import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
data = pd.read_csv('signal-data.csv')
print(data.shape)
data.head()
(1567, 592)
| Time | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ... | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | Pass/Fail | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2008-07-19 11:55:00 | 3030.93 | 2564.00 | 2187.7333 | 1411.1265 | 1.3602 | 100.0 | 97.6133 | 0.1242 | 1.5005 | ... | NaN | 0.5005 | 0.0118 | 0.0035 | 2.3630 | NaN | NaN | NaN | NaN | -1 |
| 1 | 2008-07-19 12:32:00 | 3095.78 | 2465.14 | 2230.4222 | 1463.6606 | 0.8294 | 100.0 | 102.3433 | 0.1247 | 1.4966 | ... | 208.2045 | 0.5019 | 0.0223 | 0.0055 | 4.4447 | 0.0096 | 0.0201 | 0.0060 | 208.2045 | -1 |
| 2 | 2008-07-19 13:17:00 | 2932.61 | 2559.94 | 2186.4111 | 1698.0172 | 1.5102 | 100.0 | 95.4878 | 0.1241 | 1.4436 | ... | 82.8602 | 0.4958 | 0.0157 | 0.0039 | 3.1745 | 0.0584 | 0.0484 | 0.0148 | 82.8602 | 1 |
| 3 | 2008-07-19 14:43:00 | 2988.72 | 2479.90 | 2199.0333 | 909.7926 | 1.3204 | 100.0 | 104.2367 | 0.1217 | 1.4882 | ... | 73.8432 | 0.4990 | 0.0103 | 0.0025 | 2.0544 | 0.0202 | 0.0149 | 0.0044 | 73.8432 | -1 |
| 4 | 2008-07-19 15:22:00 | 3032.24 | 2502.87 | 2233.3667 | 1326.5200 | 1.5334 | 100.0 | 100.3967 | 0.1235 | 1.5031 | ... | NaN | 0.4800 | 0.4766 | 0.1045 | 99.3032 | 0.0202 | 0.0149 | 0.0044 | 73.8432 | -1 |
5 rows × 592 columns
import plotly.graph_objects as go
import plotly.express as px
data = data.replace(np.NaN, 0)
print(data.isnull().sum())
Time 0
0 0
1 0
2 0
3 0
..
586 0
587 0
588 0
589 0
Pass/Fail 0
Length: 592, dtype: int64
data.describe().T.style.bar(
subset=['mean'],
color='Reds').background_gradient(
subset=['std'], cmap='ocean').background_gradient(subset=['50%'], cmap='PuBu')
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| 0 | 1567.000000 | 3002.910638 | 200.204648 | 0.000000 | 2965.670000 | 3010.920000 | 3056.540000 | 3356.350000 |
| 1 | 1567.000000 | 2484.700932 | 184.815753 | 0.000000 | 2451.515000 | 2498.910000 | 2538.745000 | 2846.440000 |
| 2 | 1567.000000 | 2180.887035 | 209.206773 | 0.000000 | 2180.700000 | 2200.955600 | 2218.055500 | 2315.266700 |
| 3 | 1567.000000 | 1383.901023 | 458.937272 | 0.000000 | 1080.116050 | 1283.436800 | 1590.169900 | 3715.041700 |
| 4 | 1567.000000 | 4.159516 | 56.104457 | 0.000000 | 1.011000 | 1.310100 | 1.518800 | 1114.536600 |
| 5 | 1567.000000 | 99.106573 | 9.412812 | 0.000000 | 100.000000 | 100.000000 | 100.000000 | 100.000000 |
| 6 | 1567.000000 | 100.209538 | 11.363940 | 0.000000 | 97.762200 | 101.492200 | 104.530000 | 129.252200 |
| 7 | 1567.000000 | 0.121122 | 0.012831 | 0.000000 | 0.121100 | 0.122400 | 0.123800 | 0.128600 |
| 8 | 1567.000000 | 1.460995 | 0.090461 | 0.000000 | 1.410950 | 1.461500 | 1.516850 | 1.656400 |
| 9 | 1567.000000 | -0.000840 | 0.015107 | -0.053400 | -0.010800 | -0.001300 | 0.008400 | 0.074900 |
| 10 | 1567.000000 | 0.000146 | 0.009296 | -0.034900 | -0.005600 | 0.000400 | 0.005900 | 0.053000 |
| 11 | 1567.000000 | 0.963122 | 0.036620 | 0.000000 | 0.958000 | 0.965800 | 0.971300 | 0.984800 |
| 12 | 1567.000000 | 199.701600 | 7.848224 | 0.000000 | 198.128450 | 199.525100 | 202.006750 | 272.045100 |
| 13 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 14 | 1567.000000 | 8.988130 | 2.821529 | 0.000000 | 7.080300 | 8.956500 | 10.858700 | 19.546500 |
| 15 | 1567.000000 | 412.295188 | 24.945317 | 0.000000 | 406.092900 | 412.198800 | 419.082800 | 824.927100 |
| 16 | 1567.000000 | 9.888635 | 2.440326 | 0.000000 | 9.565100 | 9.850800 | 10.127750 | 102.867700 |
| 17 | 1567.000000 | 0.969584 | 0.044155 | 0.000000 | 0.968100 | 0.972500 | 0.976800 | 0.984800 |
| 18 | 1567.000000 | 189.683511 | 8.762332 | 0.000000 | 188.291900 | 189.661500 | 192.178900 | 215.597700 |
| 19 | 1567.000000 | 12.401385 | 1.017643 | 0.000000 | 12.460000 | 12.499600 | 12.547100 | 12.989800 |
| 20 | 1567.000000 | 1.405054 | 0.016737 | 1.179700 | 1.396500 | 1.406000 | 1.415000 | 1.453400 |
| 21 | 1567.000000 | -5611.222719 | 657.774591 | -7150.250000 | -5932.625000 | -5523.000000 | -5353.500000 | 0.000000 |
| 22 | 1567.000000 | 2695.933153 | 310.647785 | 0.000000 | 2577.875000 | 2663.750000 | 2840.625000 | 3656.250000 |
| 23 | 1567.000000 | -3801.441661 | 1385.963301 | -9986.750000 | -4370.625000 | -3819.750000 | -3344.750000 | 2363.000000 |
| 24 | 1567.000000 | -298.217028 | 2900.855558 | -14804.500000 | -1474.375000 | -74.000000 | 1376.250000 | 14106.000000 |
| 25 | 1567.000000 | 1.202308 | 0.182620 | 0.000000 | 1.093900 | 1.283000 | 1.304300 | 1.382800 |
| 26 | 1567.000000 | 1.936003 | 0.201632 | 0.000000 | 1.906150 | 1.986300 | 2.003200 | 2.052800 |
| 27 | 1567.000000 | 6.630155 | 1.265856 | 0.000000 | 5.262400 | 7.264500 | 7.329600 | 7.658800 |
| 28 | 1567.000000 | 69.410828 | 4.257396 | 0.000000 | 67.377800 | 69.144400 | 72.255550 | 77.900000 |
| 29 | 1567.000000 | 2.363177 | 0.417084 | 0.000000 | 2.088900 | 2.377800 | 2.655600 | 3.511100 |
| 30 | 1567.000000 | 0.183924 | 0.033573 | 0.000000 | 0.161700 | 0.186700 | 0.207000 | 0.285100 |
| 31 | 1567.000000 | 3.668501 | 0.550829 | 0.000000 | 3.362300 | 3.430700 | 3.531250 | 4.804400 |
| 32 | 1567.000000 | 85.283010 | 2.958325 | 0.000000 | 84.484350 | 85.130500 | 85.741900 | 105.603800 |
| 33 | 1567.000000 | 8.954560 | 1.362954 | 0.000000 | 8.580000 | 8.769600 | 9.060600 | 23.345300 |
| 34 | 1567.000000 | 50.550359 | 1.740832 | 0.000000 | 50.251500 | 50.396400 | 50.578100 | 59.771100 |
| 35 | 1567.000000 | 64.514590 | 3.047065 | 0.000000 | 64.024800 | 64.165800 | 64.344700 | 94.264100 |
| 36 | 1567.000000 | 49.385834 | 1.719341 | 0.000000 | 49.420500 | 49.603600 | 49.747100 | 50.165200 |
| 37 | 1567.000000 | 66.179014 | 1.700279 | 0.000000 | 66.040500 | 66.231400 | 66.343050 | 67.958600 |
| 38 | 1567.000000 | 86.781161 | 2.238656 | 0.000000 | 86.578300 | 86.820700 | 87.002400 | 88.418800 |
| 39 | 1567.000000 | 118.603818 | 3.500339 | 0.000000 | 118.015600 | 118.397800 | 118.939600 | 133.389800 |
| 40 | 1567.000000 | 66.864885 | 25.293018 | 0.000000 | 74.240000 | 78.270000 | 80.180000 | 86.120000 |
| 41 | 1567.000000 | 3.301711 | 2.378211 | -0.075900 | 2.673000 | 3.070000 | 3.515000 | 37.880000 |
| 42 | 1567.000000 | 69.955329 | 1.768331 | 0.000000 | 70.000000 | 70.000000 | 70.000000 | 70.000000 |
| 43 | 1567.000000 | 355.312012 | 10.932313 | 0.000000 | 350.796800 | 353.714500 | 360.771800 | 377.297300 |
| 44 | 1567.000000 | 10.024763 | 0.307950 | 0.000000 | 9.925350 | 10.034700 | 10.152450 | 11.053000 |
| 45 | 1567.000000 | 136.655796 | 8.573454 | 0.000000 | 130.719100 | 136.383600 | 142.090950 | 176.313600 |
| 46 | 1567.000000 | 733.204609 | 22.170457 | 0.000000 | 724.419600 | 733.440700 | 741.449500 | 789.752300 |
| 47 | 1567.000000 | 1.177206 | 0.191898 | 0.000000 | 0.984700 | 1.250600 | 1.340200 | 1.511100 |
| 48 | 1567.000000 | 139.882906 | 5.740975 | 0.000000 | 136.900450 | 140.005500 | 143.194100 | 163.250900 |
| 49 | 1567.000000 | 0.999362 | 0.025262 | 0.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 50 | 1567.000000 | 631.850716 | 18.159656 | 0.000000 | 625.906400 | 631.362700 | 638.128150 | 667.741800 |
| 51 | 1567.000000 | 157.320531 | 61.035343 | 0.000000 | 115.476550 | 183.284200 | 206.976700 | 258.543200 |
| 52 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 53 | 1567.000000 | 4.581247 | 0.238239 | 0.000000 | 4.574000 | 4.596000 | 4.617000 | 4.764000 |
| 54 | 1567.000000 | 4.826172 | 0.251370 | 0.000000 | 4.815000 | 4.843000 | 4.869000 | 5.011000 |
| 55 | 1567.000000 | 2848.881302 | 146.441899 | 0.000000 | 2836.000000 | 2854.000000 | 2874.000000 | 2936.000000 |
| 56 | 1567.000000 | 0.926478 | 0.047374 | 0.000000 | 0.925200 | 0.931000 | 0.933100 | 0.937800 |
| 57 | 1567.000000 | 0.946792 | 0.048093 | 0.000000 | 0.946600 | 0.949300 | 0.952000 | 0.959800 |
| 58 | 1567.000000 | 4.581587 | 0.246934 | 0.000000 | 4.531900 | 4.572400 | 4.668600 | 4.847500 |
| 59 | 1567.000000 | 2.947018 | 9.512941 | -28.988200 | -1.855450 | 0.909100 | 4.337700 | 168.145500 |
| 60 | 1567.000000 | 353.799200 | 22.751550 | 0.000000 | 350.575950 | 353.777300 | 359.665450 | 373.866400 |
| 61 | 1567.000000 | 10.383233 | 0.699948 | 0.000000 | 10.281700 | 10.434600 | 10.590550 | 11.784900 |
| 62 | 1567.000000 | 116.056245 | 11.224021 | 0.000000 | 111.965950 | 116.183600 | 120.918200 | 287.150900 |
| 63 | 1567.000000 | 13.927432 | 7.164971 | 0.000000 | 10.319800 | 13.220000 | 16.325500 | 188.092300 |
| 64 | 1567.000000 | 20.450345 | 5.151917 | 0.000000 | 17.315000 | 20.007300 | 22.799550 | 48.988200 |
| 65 | 1567.000000 | 27.010614 | 7.332650 | 0.000000 | 22.994500 | 26.247000 | 29.907350 | 118.083600 |
| 66 | 1567.000000 | 703.962708 | 45.172858 | 0.000000 | 698.668100 | 706.386600 | 714.521050 | 770.608400 |
| 67 | 1567.000000 | 16.651441 | 306.914380 | 0.000000 | 0.890350 | 0.976700 | 1.064900 | 7272.828300 |
| 68 | 1567.000000 | 146.873043 | 10.043772 | 0.000000 | 145.188150 | 147.592700 | 149.935900 | 167.830900 |
| 69 | 1567.000000 | 0.996171 | 0.061780 | 0.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 70 | 1567.000000 | 616.731163 | 39.415184 | 0.000000 | 612.743200 | 619.010000 | 625.160450 | 722.601800 |
| 71 | 1567.000000 | 103.929560 | 32.242019 | 0.000000 | 87.202300 | 102.562900 | 115.439600 | 238.477500 |
| 72 | 1567.000000 | 74.173248 | 76.298333 | -59.477700 | 0.000000 | 0.000000 | 152.211700 | 175.413200 |
| 73 | 1567.000000 | 230.874137 | 234.390967 | 0.000000 | 0.000000 | 0.000000 | 466.030550 | 692.425600 |
| 74 | 1567.000000 | 0.002677 | 0.105986 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 4.195500 |
| 75 | 1567.000000 | -0.006797 | 0.022137 | -0.104900 | -0.019200 | -0.005800 | 0.006600 | 0.231500 |
| 76 | 1567.000000 | -0.028940 | 0.033145 | -0.186200 | -0.051350 | -0.028400 | -0.005250 | 0.072300 |
| 77 | 1567.000000 | -0.006934 | 0.031139 | -0.104600 | -0.029400 | -0.009400 | 0.008900 | 0.133100 |
| 78 | 1567.000000 | -0.013434 | 0.047534 | -0.348200 | -0.047300 | -0.011600 | 0.012050 | 0.249200 |
| 79 | 1567.000000 | 0.003405 | 0.022906 | -0.056800 | -0.010700 | 0.000000 | 0.012800 | 0.101300 |
| 80 | 1567.000000 | -0.018247 | 0.048900 | -0.143700 | -0.042950 | -0.008300 | 0.008700 | 0.118600 |
| 81 | 1567.000000 | -0.020829 | 0.017089 | -0.098200 | -0.027100 | -0.019400 | -0.011500 | 0.058400 |
| 82 | 1567.000000 | 0.005962 | 0.035805 | -0.212900 | -0.017350 | 0.006700 | 0.026800 | 0.143700 |
| 83 | 1567.000000 | 7.447311 | 0.549349 | 0.000000 | 7.103900 | 7.467400 | 7.807350 | 8.990400 |
| 84 | 1567.000000 | 0.132089 | 0.012651 | 0.000000 | 0.129750 | 0.133000 | 0.136300 | 0.150500 |
| 85 | 1567.000000 | 0.016266 | 0.039651 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.118400 |
| 86 | 1567.000000 | 2.401872 | 0.037332 | 2.242500 | 2.376850 | 2.403900 | 2.428600 | 2.555500 |
| 87 | 1567.000000 | 0.982420 | 0.012848 | 0.774900 | 0.975800 | 0.987400 | 0.989700 | 0.993500 |
| 88 | 1567.000000 | 1807.815021 | 53.537262 | 1627.471400 | 1777.470300 | 1809.249200 | 1841.873000 | 2105.182300 |
| 89 | 1567.000000 | 0.182562 | 0.061445 | 0.000000 | 0.167250 | 0.189300 | 0.200150 | 1.472700 |
| 90 | 1567.000000 | 8540.233496 | 1614.668409 | 0.000000 | 8542.439950 | 8803.140100 | 9055.260000 | 10746.600000 |
| 91 | 1567.000000 | 0.002431 | 0.087515 | -0.357000 | -0.042650 | 0.000000 | 0.050350 | 0.362700 |
| 92 | 1567.000000 | 0.000506 | 0.003229 | -0.012600 | -0.001150 | 0.000400 | 0.002000 | 0.028100 |
| 93 | 1567.000000 | -0.000540 | 0.003008 | -0.017100 | -0.001600 | -0.000200 | 0.001000 | 0.013300 |
| 94 | 1567.000000 | -0.000029 | 0.000174 | -0.002000 | -0.000100 | 0.000000 | 0.000100 | 0.001100 |
| 95 | 1567.000000 | 0.000060 | 0.000104 | -0.000900 | 0.000000 | 0.000000 | 0.000100 | 0.000900 |
| 96 | 1567.000000 | 0.017061 | 0.219160 | -1.480300 | -0.088400 | 0.003700 | 0.121200 | 2.509300 |
| 97 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 98 | 1567.000000 | -0.018073 | 0.426292 | -5.271700 | -0.217300 | 0.000000 | 0.188650 | 2.569800 |
| 99 | 1567.000000 | 0.001534 | 0.062620 | -0.528300 | -0.029800 | 0.000000 | 0.029800 | 0.885400 |
| 100 | 1567.000000 | -0.000021 | 0.000355 | -0.003000 | -0.000200 | 0.000000 | 0.000200 | 0.002300 |
| 101 | 1567.000000 | -0.000007 | 0.000220 | -0.002400 | -0.000100 | 0.000000 | 0.000100 | 0.001700 |
| 102 | 1567.000000 | 0.001110 | 0.062847 | -0.535300 | -0.035300 | 0.000000 | 0.033600 | 0.297900 |
| 103 | 1567.000000 | -0.009777 | 0.003082 | -0.032900 | -0.011800 | -0.010100 | -0.008200 | 0.020300 |
| 104 | 1567.000000 | -0.000015 | 0.000850 | -0.011900 | -0.000400 | 0.000000 | 0.000400 | 0.007100 |
| 105 | 1567.000000 | -0.000496 | 0.003196 | -0.028100 | -0.001900 | -0.000200 | 0.001100 | 0.012700 |
| 106 | 1567.000000 | 0.000537 | 0.002982 | -0.013300 | -0.001000 | 0.000100 | 0.001550 | 0.017200 |
| 107 | 1567.000000 | -0.001759 | 0.087307 | -0.522600 | -0.048350 | 0.000000 | 0.048600 | 0.485600 |
| 108 | 1567.000000 | -0.010747 | 0.086594 | -0.345400 | -0.064400 | -0.010500 | 0.037850 | 0.393800 |
| 109 | 1567.000000 | 0.343341 | 0.467712 | 0.000000 | 0.000000 | 0.000000 | 0.979300 | 0.984200 |
| 110 | 1567.000000 | 35.496950 | 48.365116 | 0.000000 | 0.000000 | 0.000000 | 100.627000 | 106.922700 |
| 111 | 1567.000000 | 81.217980 | 110.638438 | 0.000000 | 0.000000 | 0.000000 | 230.496350 | 236.954600 |
| 112 | 1567.000000 | 0.248770 | 0.230803 | 0.000000 | 0.000000 | 0.454900 | 0.463400 | 0.488500 |
| 113 | 1567.000000 | 0.945424 | 0.012133 | 0.853400 | 0.938600 | 0.946400 | 0.952300 | 0.976300 |
| 114 | 1567.000000 | 0.000123 | 0.001668 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.041400 |
| 115 | 1567.000000 | 747.383792 | 48.949250 | 544.025400 | 721.023000 | 750.861400 | 776.781850 | 924.531800 |
| 116 | 1567.000000 | 0.987130 | 0.009497 | 0.890000 | 0.989500 | 0.990500 | 0.990900 | 0.992400 |
| 117 | 1567.000000 | 58.625908 | 6.485174 | 52.806800 | 57.978300 | 58.549100 | 59.133900 | 311.734400 |
| 118 | 1567.000000 | 0.589246 | 0.073950 | 0.000000 | 0.593850 | 0.598900 | 0.603300 | 0.624500 |
| 119 | 1567.000000 | 0.970777 | 0.008949 | 0.841100 | 0.964800 | 0.969400 | 0.978300 | 0.982700 |
| 120 | 1567.000000 | 6.310863 | 0.124304 | 5.125900 | 6.246400 | 6.313600 | 6.375850 | 7.522000 |
| 121 | 1567.000000 | 15.705699 | 1.198204 | 0.000000 | 15.730000 | 15.790000 | 15.860000 | 16.070000 |
| 122 | 1567.000000 | 3.875999 | 0.948460 | 0.000000 | 3.193000 | 3.865000 | 4.392000 | 6.889000 |
| 123 | 1567.000000 | 15.738743 | 1.201456 | 0.000000 | 15.760000 | 15.830000 | 15.900000 | 16.100000 |
| 124 | 1567.000000 | 15.703989 | 1.199362 | 0.000000 | 15.720000 | 15.780000 | 15.870000 | 16.100000 |
| 125 | 1567.000000 | 1.178150 | 0.293738 | 0.000000 | 0.964900 | 1.135000 | 1.338000 | 2.465000 |
| 126 | 1567.000000 | 2.734930 | 0.327283 | 0.000000 | 2.567000 | 2.735000 | 2.873000 | 3.991000 |
| 127 | 1567.000000 | 0.644753 | 0.143642 | 0.000000 | 0.547250 | 0.653800 | 0.712400 | 1.175000 |
| 128 | 1567.000000 | 3.173848 | 0.357231 | 0.000000 | 3.074000 | 3.195000 | 3.311000 | 3.895000 |
| 129 | 1567.000000 | -0.551045 | 1.217687 | -3.779000 | -0.898800 | -0.141900 | 0.047300 | 2.458000 |
| 130 | 1567.000000 | 0.740698 | 0.099717 | 0.000000 | 0.687900 | 0.758600 | 0.814500 | 0.888400 |
| 131 | 1567.000000 | 0.992077 | 0.075459 | 0.000000 | 0.996400 | 0.997700 | 0.998900 | 1.019000 |
| 132 | 1567.000000 | 2.306708 | 0.173595 | 0.000000 | 2.277100 | 2.312200 | 2.358300 | 2.472300 |
| 133 | 1567.000000 | 998.917156 | 71.876145 | 0.000000 | 999.939100 | 1004.028100 | 1008.670600 | 1020.994400 |
| 134 | 1567.000000 | 39.190871 | 4.096814 | 0.000000 | 37.297200 | 38.902600 | 40.804600 | 64.128700 |
| 135 | 1567.000000 | 117.584556 | 57.836817 | 0.000000 | 91.000000 | 109.000000 | 127.000000 | 994.000000 |
| 136 | 1567.000000 | 137.665603 | 54.479555 | 0.000000 | 89.600000 | 134.200000 | 180.900000 | 295.800000 |
| 137 | 1567.000000 | 122.144863 | 52.774629 | 0.000000 | 80.800000 | 117.000000 | 161.600000 | 334.700000 |
| 138 | 1567.000000 | 57.088384 | 13.432949 | 0.000000 | 50.599900 | 55.700200 | 62.900100 | 141.799800 |
| 139 | 1567.000000 | 413.043455 | 265.040342 | 0.000000 | 240.293950 | 333.975100 | 494.806000 | 1770.690900 |
| 140 | 1567.000000 | 25.844917 | 504.657054 | 0.000000 | 0.129700 | 0.234200 | 0.434800 | 9998.894400 |
| 141 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 142 | 1567.000000 | 6.582227 | 3.591173 | 0.000000 | 5.070000 | 6.240000 | 7.500000 | 103.390000 |
| 143 | 1567.000000 | 0.004146 | 0.001316 | 0.000000 | 0.003300 | 0.003900 | 0.004900 | 0.012100 |
| 144 | 1567.000000 | 0.119855 | 0.061453 | 0.000000 | 0.083900 | 0.107400 | 0.132650 | 0.625300 |
| 145 | 1567.000000 | 0.063540 | 0.026621 | 0.000000 | 0.048000 | 0.058600 | 0.071800 | 0.250700 |
| 146 | 1567.000000 | 0.054940 | 0.021919 | 0.000000 | 0.042300 | 0.050000 | 0.061500 | 0.247900 |
| 147 | 1567.000000 | 0.017389 | 0.027113 | 0.000000 | 0.010000 | 0.015900 | 0.021300 | 0.978300 |
| 148 | 1567.000000 | 8.460496 | 18.731104 | 0.000000 | 6.357700 | 7.916200 | 9.581850 | 742.942100 |
| 149 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 150 | 1567.000000 | 6.801222 | 3.252414 | 0.000000 | 4.444500 | 5.948000 | 8.269500 | 22.318000 |
| 151 | 1567.000000 | 14.020509 | 30.978921 | 0.000000 | 8.076500 | 10.987000 | 14.342000 | 536.564000 |
| 152 | 1567.000000 | 1.194442 | 23.341731 | 0.000000 | 0.372850 | 0.467500 | 0.677500 | 924.378000 |
| 153 | 1567.000000 | 0.011904 | 0.009351 | 0.000000 | 0.007200 | 0.011100 | 0.014900 | 0.238900 |
| 154 | 1567.000000 | 7.683233 | 5.245011 | 0.000000 | 5.912750 | 7.509800 | 9.050950 | 191.547800 |
| 155 | 1567.000000 | 0.503935 | 1.119566 | 0.000000 | 0.240000 | 0.320000 | 0.450000 | 12.710000 |
| 156 | 1567.000000 | 0.058089 | 0.079174 | 0.011100 | 0.036250 | 0.048700 | 0.066700 | 2.201600 |
| 157 | 1567.000000 | 0.004148 | 0.017750 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.287600 |
| 158 | 1567.000000 | 91.558265 | 318.342602 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 2505.299800 |
| 159 | 1567.000000 | 881.553925 | 982.920734 | 0.000000 | 411.000000 | 621.000000 | 963.500000 | 7791.000000 |
| 160 | 1567.000000 | 554.637524 | 574.783715 | 0.000000 | 294.500000 | 437.000000 | 624.500000 | 4170.000000 |
| 161 | 1567.000000 | 4061.659860 | 4239.026177 | 0.000000 | 1310.500000 | 2606.000000 | 5033.000000 | 37943.000000 |
| 162 | 1567.000000 | 4791.031908 | 6551.623577 | 0.000000 | 445.000000 | 1781.000000 | 6376.000000 | 36871.000000 |
| 163 | 1567.000000 | 0.140026 | 0.122014 | 0.000000 | 0.091000 | 0.120000 | 0.154000 | 0.957000 |
| 164 | 1567.000000 | 0.127779 | 0.242422 | 0.000000 | 0.068000 | 0.089000 | 0.116000 | 1.817000 |
| 165 | 1567.000000 | 0.251704 | 0.407169 | 0.000000 | 0.132000 | 0.184000 | 0.254500 | 3.286000 |
| 166 | 1567.000000 | 2.785322 | 1.123465 | 0.000000 | 2.100000 | 2.600000 | 3.200000 | 21.100000 |
| 167 | 1567.000000 | 1.234205 | 0.633901 | 0.000000 | 0.900000 | 1.200000 | 1.500000 | 16.300000 |
| 168 | 1567.000000 | 0.124238 | 0.047815 | 0.000000 | 0.090000 | 0.119000 | 0.150500 | 0.725000 |
| 169 | 1567.000000 | 0.399943 | 0.198308 | 0.000000 | 0.229500 | 0.411000 | 0.536000 | 1.143000 |
| 170 | 1567.000000 | 0.683894 | 0.158364 | 0.000000 | 0.575600 | 0.686000 | 0.797300 | 1.153000 |
| 171 | 1567.000000 | 0.119987 | 0.060841 | 0.000000 | 0.079800 | 0.112500 | 0.140300 | 0.494000 |
| 172 | 1567.000000 | 0.319908 | 0.071678 | 0.000000 | 0.276600 | 0.323600 | 0.370200 | 0.548400 |
| 173 | 1567.000000 | 0.575824 | 0.096804 | 0.000000 | 0.516700 | 0.576700 | 0.634500 | 0.864300 |
| 174 | 1567.000000 | 0.319908 | 0.071682 | 0.000000 | 0.276500 | 0.323600 | 0.370200 | 0.548400 |
| 175 | 1567.000000 | 0.777547 | 0.117934 | 0.000000 | 0.691900 | 0.768200 | 0.843900 | 1.172000 |
| 176 | 1567.000000 | 0.244562 | 0.075149 | 0.000000 | 0.196200 | 0.242900 | 0.293750 | 0.441100 |
| 177 | 1567.000000 | 0.394508 | 0.282988 | 0.000000 | 0.222000 | 0.299000 | 0.423000 | 1.858000 |
| 178 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 179 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 180 | 1567.000000 | 19.001123 | 3.345236 | 0.000000 | 16.845000 | 18.690000 | 20.965000 | 48.670000 |
| 181 | 1567.000000 | 0.546421 | 0.224755 | 0.000000 | 0.378000 | 0.524000 | 0.688500 | 3.573000 |
| 182 | 1567.000000 | 10.773663 | 4.171620 | 0.000000 | 7.730000 | 10.160000 | 13.335000 | 55.000000 |
| 183 | 1567.000000 | 26.644156 | 6.867026 | 0.000000 | 21.161000 | 27.197000 | 31.687000 | 72.947000 |
| 184 | 1567.000000 | 0.144723 | 0.110223 | 0.000000 | 0.102150 | 0.132500 | 0.169100 | 3.228300 |
| 185 | 1567.000000 | 7.361040 | 7.188833 | 0.000000 | 5.380000 | 6.730000 | 8.450000 | 267.910000 |
| 186 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 187 | 1567.000000 | 17.924844 | 8.619080 | 0.000000 | 14.500000 | 17.860000 | 20.860000 | 307.930000 |
| 188 | 1567.000000 | 43.183842 | 21.732375 | 0.000000 | 24.652500 | 40.203000 | 57.672500 | 191.830000 |
| 189 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 190 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 191 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 192 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 193 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 194 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 195 | 1567.000000 | 0.286352 | 0.394948 | 0.000000 | 0.217000 | 0.259000 | 0.296000 | 4.838000 |
| 196 | 1567.000000 | 8.649675 | 15.696455 | 0.000000 | 5.020000 | 6.770000 | 9.510000 | 396.110000 |
| 197 | 1567.000000 | 20.015775 | 10.604828 | 0.000000 | 17.105000 | 19.360000 | 21.450000 | 252.870000 |
| 198 | 1567.000000 | 0.555225 | 0.537778 | 0.000000 | 0.295500 | 0.422000 | 0.724500 | 10.017000 |
| 199 | 1567.000000 | 11.487900 | 16.429475 | 0.000000 | 6.730000 | 8.550000 | 11.425000 | 390.120000 |
| 200 | 1567.000000 | 17.521570 | 8.750397 | 0.000000 | 14.100000 | 17.210000 | 20.160000 | 199.620000 |
| 201 | 1567.000000 | 7.804340 | 5.119851 | 0.000000 | 4.990000 | 6.740000 | 9.485000 | 126.530000 |
| 202 | 1567.000000 | 10.125031 | 14.605952 | 0.000000 | 6.068000 | 8.454000 | 11.931950 | 490.561000 |
| 203 | 1567.000000 | 29.957993 | 17.527064 | 0.000000 | 24.618500 | 30.085000 | 33.504500 | 500.349000 |
| 204 | 1567.000000 | 32.094806 | 564.021142 | 0.000000 | 0.113600 | 0.158000 | 0.230600 | 9998.448300 |
| 205 | 1567.000000 | 9.015469 | 11.532514 | 0.000000 | 6.020000 | 7.720000 | 9.930000 | 320.050000 |
| 206 | 1567.000000 | 0.001276 | 0.050524 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 2.000000 |
| 207 | 1567.000000 | 20.298156 | 17.509315 | 0.000000 | 16.320000 | 19.710000 | 22.365000 | 457.650000 |
| 208 | 1567.000000 | 72.983789 | 28.376632 | 0.000000 | 55.861000 | 73.154000 | 90.452500 | 172.349000 |
| 209 | 1567.000000 | 0.029451 | 1.165835 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 46.150000 |
| 210 | 1567.000000 | 0.087505 | 0.043145 | 0.000000 | 0.064850 | 0.078900 | 0.099050 | 0.516400 |
| 211 | 1567.000000 | 0.055886 | 0.025774 | 0.000000 | 0.043200 | 0.053000 | 0.064100 | 0.322700 |
| 212 | 1567.000000 | 0.050644 | 0.031965 | 0.000000 | 0.032000 | 0.040700 | 0.062100 | 0.594100 |
| 213 | 1567.000000 | 0.059422 | 0.053141 | 0.000000 | 0.035400 | 0.055500 | 0.073400 | 1.283700 |
| 214 | 1567.000000 | 0.081993 | 0.056948 | 0.000000 | 0.055900 | 0.074500 | 0.093250 | 0.761500 |
| 215 | 1567.000000 | 0.079834 | 0.031802 | 0.000000 | 0.061850 | 0.082200 | 0.098100 | 0.342900 |
| 216 | 1567.000000 | 0.082205 | 0.027546 | 0.000000 | 0.068450 | 0.084400 | 0.097300 | 0.282800 |
| 217 | 1567.000000 | 0.070538 | 0.046763 | 0.000000 | 0.044950 | 0.061200 | 0.086050 | 0.674400 |
| 218 | 1567.000000 | 3.769059 | 1.173935 | 0.000000 | 2.945900 | 3.630000 | 4.403400 | 8.801500 |
| 219 | 1567.000000 | 0.003229 | 0.001664 | 0.000000 | 0.002200 | 0.003000 | 0.003800 | 0.016300 |
| 220 | 1567.000000 | 0.001329 | 0.003324 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.024000 |
| 221 | 1567.000000 | 0.060718 | 0.023305 | 0.020000 | 0.040200 | 0.060900 | 0.076500 | 0.230500 |
| 222 | 1567.000000 | 0.008821 | 0.055937 | 0.000300 | 0.001400 | 0.002300 | 0.005500 | 0.991100 |
| 223 | 1567.000000 | 122.846571 | 55.156003 | 32.263700 | 95.147350 | 119.436000 | 144.502800 | 1768.880200 |
| 224 | 1567.000000 | 0.057438 | 0.070830 | 0.000000 | 0.028600 | 0.039100 | 0.059200 | 1.436100 |
| 225 | 1567.000000 | 1007.174082 | 464.405993 | 0.000000 | 692.949700 | 944.900400 | 1252.399650 | 3601.299800 |
| 226 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 227 | 1567.000000 | 0.019101 | 0.010771 | 0.000000 | 0.013200 | 0.016500 | 0.021200 | 0.154100 |
| 228 | 1567.000000 | 0.017822 | 0.010757 | 0.000000 | 0.012600 | 0.015400 | 0.020000 | 0.213300 |
| 229 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 230 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 231 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 232 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 233 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 234 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 235 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 236 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 237 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 238 | 1567.000000 | 0.004785 | 0.001705 | 0.000000 | 0.003700 | 0.004600 | 0.005700 | 0.024400 |
| 239 | 1567.000000 | 0.004569 | 0.001450 | 0.000000 | 0.003600 | 0.004400 | 0.005300 | 0.023600 |
| 240 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 241 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 242 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 243 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 244 | 1567.000000 | 0.002016 | 0.050131 | 0.000000 | 0.000000 | 0.000000 | 0.001300 | 1.984400 |
| 245 | 1567.000000 | 0.606010 | 2.694320 | 0.000000 | 0.000000 | 0.000000 | 0.940600 | 99.902200 |
| 246 | 1567.000000 | 1.453516 | 6.263378 | 0.000000 | 0.000000 | 0.000000 | 2.882100 | 237.183700 |
| 247 | 1567.000000 | 0.029020 | 0.056017 | 0.000000 | 0.000000 | 0.015000 | 0.030100 | 0.491400 |
| 248 | 1567.000000 | 0.025171 | 0.049235 | 0.003000 | 0.014700 | 0.021000 | 0.027300 | 0.973200 |
| 249 | 1567.000000 | 0.001065 | 0.015771 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.413800 |
| 250 | 1567.000000 | 109.650967 | 54.597274 | 21.010700 | 76.132150 | 103.093600 | 131.758400 | 1119.704200 |
| 251 | 1567.000000 | 0.004285 | 0.037472 | 0.000300 | 0.000700 | 0.001000 | 0.001300 | 0.990900 |
| 252 | 1567.000000 | 4.645115 | 64.354756 | 0.767300 | 2.205650 | 2.864600 | 3.795050 | 2549.988500 |
| 253 | 1567.000000 | 0.032707 | 0.022624 | 0.000000 | 0.024200 | 0.030600 | 0.037700 | 0.451700 |
| 254 | 1567.000000 | 0.013943 | 0.009132 | 0.001700 | 0.004700 | 0.015000 | 0.021300 | 0.078700 |
| 255 | 1567.000000 | 0.403848 | 0.120334 | 0.126900 | 0.307600 | 0.405100 | 0.480950 | 0.925500 |
| 256 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 257 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 258 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 259 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 260 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 261 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 262 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 263 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 264 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 265 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 266 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 267 | 1567.000000 | 0.070227 | 0.029998 | 0.000000 | 0.044000 | 0.069900 | 0.091600 | 0.157800 |
| 268 | 1567.000000 | 19.405100 | 7.456424 | 0.000000 | 13.720000 | 17.977000 | 24.653000 | 40.855000 |
| 269 | 1567.000000 | 3.758579 | 1.180516 | 0.000000 | 2.905700 | 3.691200 | 4.376800 | 10.152900 |
| 270 | 1567.000000 | 29.166926 | 8.549462 | 0.000000 | 24.929500 | 28.727500 | 31.691650 | 158.526000 |
| 271 | 1567.000000 | 45.880249 | 18.057760 | 0.000000 | 29.742850 | 45.493400 | 59.484150 | 132.647900 |
| 272 | 1567.000000 | 41.113663 | 17.910966 | 0.000000 | 26.953750 | 39.835400 | 54.166500 | 122.117400 |
| 273 | 1567.000000 | 20.000941 | 4.260263 | 0.000000 | 18.233700 | 19.554900 | 22.089100 | 43.573700 |
| 274 | 1567.000000 | 135.074752 | 86.184432 | 0.000000 | 80.607400 | 110.231200 | 161.979100 | 659.169600 |
| 275 | 1567.000000 | 8.615545 | 168.194506 | 0.000000 | 0.044050 | 0.077300 | 0.144900 | 3332.596400 |
| 276 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 277 | 1567.000000 | 2.190993 | 1.209119 | 0.000000 | 1.691800 | 2.078100 | 2.513100 | 32.170900 |
| 278 | 1567.000000 | 0.001111 | 0.000349 | 0.000000 | 0.000900 | 0.001100 | 0.001300 | 0.003400 |
| 279 | 1567.000000 | 0.041004 | 0.020329 | 0.000000 | 0.028300 | 0.037100 | 0.045750 | 0.188400 |
| 280 | 1567.000000 | 0.018011 | 0.006511 | 0.000000 | 0.014100 | 0.016900 | 0.020700 | 0.075500 |
| 281 | 1567.000000 | 0.015075 | 0.005568 | 0.000000 | 0.011900 | 0.013900 | 0.016600 | 0.059700 |
| 282 | 1567.000000 | 0.005762 | 0.008547 | 0.000000 | 0.003300 | 0.005300 | 0.007100 | 0.308300 |
| 283 | 1567.000000 | 2.800405 | 5.861433 | 0.000000 | 2.208850 | 2.657100 | 3.145700 | 232.804900 |
| 284 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 285 | 1567.000000 | 2.115737 | 0.966455 | 0.000000 | 1.432500 | 1.871300 | 2.605900 | 6.869800 |
| 286 | 1567.000000 | 4.251862 | 9.756251 | 0.000000 | 2.456050 | 3.356100 | 4.306600 | 207.016100 |
| 287 | 1567.000000 | 0.366826 | 7.379282 | 0.000000 | 0.114750 | 0.138800 | 0.198400 | 292.227400 |
| 288 | 1567.000000 | 0.003916 | 0.002938 | 0.000000 | 0.002400 | 0.003600 | 0.004900 | 0.074900 |
| 289 | 1567.000000 | 2.573659 | 1.619374 | 0.000000 | 2.086300 | 2.547600 | 3.023800 | 59.518700 |
| 290 | 1567.000000 | 0.122639 | 0.270299 | 0.000000 | 0.064550 | 0.083200 | 0.117550 | 4.420300 |
| 291 | 1567.000000 | 0.019926 | 0.025549 | 0.003800 | 0.012500 | 0.016900 | 0.023600 | 0.691500 |
| 292 | 1567.000000 | 0.001276 | 0.005331 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.083100 |
| 293 | 1567.000000 | 29.550772 | 103.474398 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 879.226000 |
| 294 | 1567.000000 | 401.301904 | 476.961283 | 0.000000 | 184.931400 | 278.340900 | 428.515800 | 3933.755000 |
| 295 | 1567.000000 | 252.676209 | 283.493622 | 0.000000 | 129.659800 | 195.667200 | 273.865150 | 2005.874400 |
| 296 | 1567.000000 | 1876.829864 | 1974.990421 | 0.000000 | 600.426350 | 1202.103000 | 2337.950650 | 15559.952500 |
| 297 | 1567.000000 | 2339.836772 | 3225.948324 | 0.000000 | 206.423050 | 819.184300 | 3188.190750 | 18520.468300 |
| 298 | 1567.000000 | 0.063723 | 0.064224 | 0.000000 | 0.040650 | 0.052700 | 0.069200 | 0.526400 |
| 299 | 1567.000000 | 0.060190 | 0.130760 | 0.000000 | 0.030200 | 0.040000 | 0.052000 | 1.031200 |
| 300 | 1567.000000 | 0.118235 | 0.219048 | 0.000000 | 0.058900 | 0.082700 | 0.115350 | 1.812300 |
| 301 | 1567.000000 | 0.908984 | 0.333358 | 0.000000 | 0.717200 | 0.860400 | 1.046400 | 5.711000 |
| 302 | 1567.000000 | 0.402828 | 0.197913 | 0.000000 | 0.295800 | 0.380800 | 0.476700 | 5.154900 |
| 303 | 1567.000000 | 0.040292 | 0.014573 | 0.000000 | 0.029950 | 0.038800 | 0.048600 | 0.225800 |
| 304 | 1567.000000 | 0.131908 | 0.064997 | 0.000000 | 0.071950 | 0.137100 | 0.178500 | 0.333700 |
| 305 | 1567.000000 | 0.264748 | 0.057758 | 0.000000 | 0.225000 | 0.264300 | 0.307300 | 0.475000 |
| 306 | 1567.000000 | 0.048592 | 0.025422 | 0.000000 | 0.033100 | 0.044800 | 0.055100 | 0.224600 |
| 307 | 1567.000000 | 0.128839 | 0.027651 | 0.000000 | 0.113500 | 0.129500 | 0.147600 | 0.211200 |
| 308 | 1567.000000 | 0.218275 | 0.034033 | 0.000000 | 0.197600 | 0.219400 | 0.237900 | 0.323900 |
| 309 | 1567.000000 | 0.128839 | 0.027654 | 0.000000 | 0.113500 | 0.129500 | 0.147600 | 0.211200 |
| 310 | 1567.000000 | 0.304557 | 0.044123 | 0.000000 | 0.278500 | 0.302900 | 0.331900 | 0.443800 |
| 311 | 1567.000000 | 0.097282 | 0.028892 | 0.000000 | 0.077450 | 0.097700 | 0.115900 | 0.178400 |
| 312 | 1567.000000 | 0.159949 | 0.117348 | 0.000000 | 0.091500 | 0.121400 | 0.160150 | 0.754900 |
| 313 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 314 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 315 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 316 | 1567.000000 | 5.973163 | 1.029437 | 0.000000 | 5.300400 | 5.830700 | 6.546900 | 13.095800 |
| 317 | 1567.000000 | 0.172519 | 0.072501 | 0.000000 | 0.117250 | 0.163200 | 0.218100 | 1.003400 |
| 318 | 1567.000000 | 3.186736 | 1.218208 | 0.000000 | 2.318850 | 2.896700 | 4.021200 | 15.893400 |
| 319 | 1567.000000 | 7.910984 | 2.187522 | 0.000000 | 6.236100 | 8.387600 | 9.480800 | 20.045500 |
| 320 | 1567.000000 | 0.043077 | 0.031893 | 0.000000 | 0.031200 | 0.039800 | 0.050200 | 0.947400 |
| 321 | 1567.000000 | 2.262283 | 2.117091 | 0.000000 | 1.668900 | 2.076600 | 2.632900 | 79.151500 |
| 322 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 323 | 1567.000000 | 5.389978 | 2.521738 | 0.000000 | 4.272400 | 5.458100 | 6.344350 | 89.191700 |
| 324 | 1567.000000 | 13.323664 | 6.622307 | 0.000000 | 7.565650 | 12.498100 | 17.925150 | 51.867800 |
| 325 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 326 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 327 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 328 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 329 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 330 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 331 | 1567.000000 | 0.083019 | 0.063483 | 0.000000 | 0.068600 | 0.084800 | 0.095600 | 1.095900 |
| 332 | 1567.000000 | 2.581899 | 5.635251 | 0.000000 | 1.542600 | 2.055300 | 2.789300 | 174.894400 |
| 333 | 1567.000000 | 6.192065 | 3.418558 | 0.000000 | 5.446650 | 5.977600 | 6.544500 | 90.515900 |
| 334 | 1567.000000 | 0.167719 | 0.172864 | 0.000000 | 0.088850 | 0.129100 | 0.210150 | 3.412500 |
| 335 | 1567.000000 | 3.413804 | 5.774355 | 0.000000 | 2.025650 | 2.508900 | 3.355500 | 172.711900 |
| 336 | 1567.000000 | 9.692893 | 7.567149 | 0.000000 | 8.281600 | 9.068300 | 10.034700 | 214.862800 |
| 337 | 1567.000000 | 2.317084 | 1.702726 | 0.000000 | 1.530650 | 2.053800 | 2.779950 | 38.899500 |
| 338 | 1567.000000 | 3.024011 | 5.636035 | 0.000000 | 1.898650 | 2.553700 | 3.397900 | 196.688000 |
| 339 | 1567.000000 | 9.293237 | 6.090385 | 0.000000 | 7.535050 | 9.462100 | 10.438250 | 197.498800 |
| 340 | 1567.000000 | 14.617322 | 261.238129 | 0.000000 | 0.034500 | 0.046300 | 0.066800 | 5043.878900 |
| 341 | 1567.000000 | 2.721633 | 3.664758 | 0.000000 | 1.901650 | 2.374800 | 2.984400 | 97.708900 |
| 342 | 1567.000000 | 0.000285 | 0.011297 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.447200 |
| 343 | 1567.000000 | 6.174774 | 5.375183 | 0.000000 | 4.978700 | 6.001300 | 6.881050 | 156.336000 |
| 344 | 1567.000000 | 23.128248 | 8.993284 | 0.000000 | 17.799100 | 23.175300 | 28.852650 | 59.324100 |
| 345 | 1567.000000 | 3.925861 | 12.924349 | 0.000000 | 0.000000 | 0.000000 | 5.539250 | 257.010600 |
| 346 | 1567.000000 | 2.846441 | 12.332865 | 0.000000 | 0.000000 | 0.000000 | 3.034000 | 187.758900 |
| 347 | 1567.000000 | 0.008880 | 0.351511 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 13.914700 |
| 348 | 1567.000000 | 0.024327 | 0.012156 | 0.000000 | 0.017900 | 0.022500 | 0.027300 | 0.220000 |
| 349 | 1567.000000 | 0.024865 | 0.010969 | 0.000000 | 0.019400 | 0.023800 | 0.028500 | 0.133900 |
| 350 | 1567.000000 | 0.022847 | 0.014498 | 0.000000 | 0.014400 | 0.018600 | 0.028100 | 0.291400 |
| 351 | 1567.000000 | 0.027162 | 0.024608 | 0.000000 | 0.016000 | 0.025100 | 0.033600 | 0.618800 |
| 352 | 1567.000000 | 0.022998 | 0.013367 | 0.000000 | 0.015900 | 0.021800 | 0.026800 | 0.142900 |
| 353 | 1567.000000 | 0.039713 | 0.016158 | 0.000000 | 0.029250 | 0.041800 | 0.050100 | 0.153500 |
| 354 | 1567.000000 | 0.041279 | 0.013953 | 0.000000 | 0.033900 | 0.043900 | 0.049900 | 0.134400 |
| 355 | 1567.000000 | 0.034014 | 0.022538 | 0.000000 | 0.021000 | 0.028900 | 0.041900 | 0.278900 |
| 356 | 1567.000000 | 1.297800 | 0.388183 | 0.000000 | 1.025150 | 1.255200 | 1.533250 | 2.834800 |
| 357 | 1567.000000 | 0.000991 | 0.000507 | 0.000000 | 0.000700 | 0.000900 | 0.001100 | 0.005200 |
| 358 | 1567.000000 | 0.000352 | 0.000871 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.004700 |
| 359 | 1567.000000 | 0.019840 | 0.007136 | 0.007600 | 0.013800 | 0.019600 | 0.025000 | 0.088800 |
| 360 | 1567.000000 | 0.002945 | 0.020003 | 0.000100 | 0.000400 | 0.000700 | 0.001800 | 0.409000 |
| 361 | 1567.000000 | 39.936406 | 17.056304 | 10.720400 | 32.168700 | 39.696100 | 47.079200 | 547.172200 |
| 362 | 1567.000000 | 0.017785 | 0.021537 | 0.000000 | 0.009200 | 0.012300 | 0.018300 | 0.416300 |
| 363 | 1567.000000 | 322.471292 | 148.791939 | 0.000000 | 220.732900 | 304.498100 | 409.116550 | 1072.203100 |
| 364 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 365 | 1567.000000 | 0.005192 | 0.002661 | 0.000000 | 0.003800 | 0.004600 | 0.005800 | 0.036800 |
| 366 | 1567.000000 | 0.004808 | 0.002387 | 0.000000 | 0.003500 | 0.004300 | 0.005400 | 0.039200 |
| 367 | 1567.000000 | 0.003759 | 0.002704 | 0.000000 | 0.002600 | 0.003200 | 0.004200 | 0.035700 |
| 368 | 1567.000000 | 0.003159 | 0.002112 | 0.000000 | 0.002200 | 0.002800 | 0.003600 | 0.033400 |
| 369 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 370 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 371 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 372 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 373 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 374 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 375 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 376 | 1567.000000 | 0.001599 | 0.000537 | 0.000000 | 0.001300 | 0.001600 | 0.001900 | 0.008200 |
| 377 | 1567.000000 | 0.001569 | 0.000470 | 0.000000 | 0.001300 | 0.001500 | 0.001800 | 0.007700 |
| 378 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 379 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 380 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 381 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 382 | 1567.000000 | 0.000640 | 0.015842 | 0.000000 | 0.000000 | 0.000000 | 0.000400 | 0.627100 |
| 383 | 1567.000000 | 0.189554 | 0.834248 | 0.000000 | 0.000000 | 0.000000 | 0.303450 | 30.998200 |
| 384 | 1567.000000 | 0.450358 | 1.972135 | 0.000000 | 0.000000 | 0.000000 | 0.873900 | 74.844500 |
| 385 | 1567.000000 | 0.006213 | 0.012023 | 0.000000 | 0.000000 | 0.004300 | 0.007150 | 0.207300 |
| 386 | 1567.000000 | 0.008281 | 0.015488 | 0.000800 | 0.004800 | 0.006800 | 0.009300 | 0.306800 |
| 387 | 1567.000000 | 0.000339 | 0.004989 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.130900 |
| 388 | 1567.000000 | 35.155091 | 17.227003 | 6.310100 | 24.386550 | 32.530700 | 42.652450 | 348.829300 |
| 389 | 1567.000000 | 0.001338 | 0.011816 | 0.000100 | 0.000200 | 0.000300 | 0.000400 | 0.312700 |
| 390 | 1567.000000 | 1.431868 | 20.326415 | 0.304600 | 0.675150 | 0.877300 | 1.148200 | 805.393600 |
| 391 | 1567.000000 | 0.010788 | 0.006820 | 0.000000 | 0.008200 | 0.010200 | 0.012400 | 0.137500 |
| 392 | 1567.000000 | 0.004533 | 0.002956 | 0.000500 | 0.001500 | 0.004900 | 0.006900 | 0.022900 |
| 393 | 1567.000000 | 0.133990 | 0.038408 | 0.034200 | 0.104400 | 0.133900 | 0.160400 | 0.299400 |
| 394 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 395 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 396 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 397 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 398 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 399 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 400 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 401 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 402 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 403 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 404 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 405 | 1567.000000 | 0.024084 | 0.010839 | 0.000000 | 0.013800 | 0.023900 | 0.032300 | 0.051400 |
| 406 | 1567.000000 | 6.696253 | 2.862845 | 0.000000 | 4.522400 | 5.914400 | 8.563000 | 14.727700 |
| 407 | 1567.000000 | 1.225708 | 0.374231 | 0.000000 | 0.965600 | 1.237400 | 1.416700 | 3.312800 |
| 408 | 1567.000000 | 5.323890 | 2.591574 | 0.000000 | 4.126000 | 4.921200 | 5.787100 | 44.310000 |
| 409 | 1567.000000 | 4.562892 | 1.795871 | 0.000000 | 2.993050 | 4.478600 | 5.929950 | 9.576500 |
| 410 | 1567.000000 | 4.907324 | 2.143599 | 0.000000 | 3.242000 | 4.711900 | 6.453800 | 13.807100 |
| 411 | 1567.000000 | 2.592714 | 0.601700 | 0.000000 | 2.300400 | 2.541800 | 2.848450 | 6.215000 |
| 412 | 1567.000000 | 30.635146 | 18.560608 | 0.000000 | 18.153750 | 25.970400 | 38.026900 | 128.281600 |
| 413 | 1567.000000 | 25.383859 | 47.158186 | 0.000000 | 11.283850 | 19.882700 | 29.307300 | 899.119000 |
| 414 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 415 | 1567.000000 | 6.571376 | 3.989757 | 0.000000 | 4.917300 | 6.158200 | 7.545300 | 116.861500 |
| 416 | 1567.000000 | 3.384796 | 1.064042 | 0.000000 | 2.655150 | 3.229800 | 4.010700 | 9.690000 |
| 417 | 1567.000000 | 8.180451 | 4.062471 | 0.000000 | 5.760400 | 7.388100 | 9.167850 | 39.037600 |
| 418 | 1567.000000 | 319.850481 | 287.748118 | 0.000000 | 0.000000 | 301.721400 | 523.624450 | 999.316000 |
| 419 | 1567.000000 | 308.666837 | 325.427750 | 0.000000 | 0.000000 | 271.835100 | 582.803100 | 998.681300 |
| 420 | 1567.000000 | 1.818937 | 3.056431 | 0.000000 | 1.029450 | 1.644200 | 2.214600 | 111.495600 |
| 421 | 1567.000000 | 4.169195 | 6.911047 | 0.000000 | 3.178050 | 3.942600 | 4.783200 | 273.095200 |
| 422 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 423 | 1567.000000 | 77.511766 | 32.742270 | 0.000000 | 55.864100 | 69.718200 | 92.832750 | 424.215200 |
| 424 | 1567.000000 | 3.309121 | 6.320966 | 0.000000 | 1.963050 | 2.665800 | 3.469200 | 103.180900 |
| 425 | 1567.000000 | 6.783301 | 23.237328 | 0.000000 | 3.756900 | 4.763500 | 6.873850 | 898.608500 |
| 426 | 1567.000000 | 1.231495 | 0.996128 | 0.000000 | 0.740400 | 1.135100 | 1.538850 | 24.990400 |
| 427 | 1567.000000 | 4.050731 | 3.044406 | 0.000000 | 3.108250 | 3.940100 | 4.767950 | 113.223000 |
| 428 | 1567.000000 | 4.193812 | 10.604058 | 0.000000 | 1.930700 | 2.534100 | 3.609000 | 118.753300 |
| 429 | 1567.000000 | 4.171844 | 6.435390 | 0.783700 | 2.571400 | 3.453800 | 4.755800 | 186.616400 |
| 430 | 1567.000000 | 18.398088 | 36.043055 | 0.000000 | 6.993900 | 11.082600 | 17.402050 | 400.000000 |
| 431 | 1567.000000 | 22.329768 | 36.380923 | 0.000000 | 11.054050 | 16.350100 | 21.739650 | 400.000000 |
| 432 | 1567.000000 | 99.240807 | 126.158034 | 0.000000 | 30.913150 | 57.928600 | 120.136900 | 994.285700 |
| 433 | 1567.000000 | 205.256995 | 225.754003 | 0.000000 | 9.930500 | 150.978800 | 304.541800 | 995.744700 |
| 434 | 1567.000000 | 14.715140 | 34.091128 | 0.000000 | 7.532700 | 10.188600 | 12.752800 | 400.000000 |
| 435 | 1567.000000 | 9.358706 | 34.349465 | 0.000000 | 3.486700 | 4.550000 | 5.822150 | 400.000000 |
| 436 | 1567.000000 | 7.503677 | 34.536772 | 0.000000 | 1.943300 | 2.762600 | 3.821250 | 400.000000 |
| 437 | 1567.000000 | 4.011659 | 1.616622 | 0.000000 | 3.065600 | 3.780400 | 4.678250 | 32.274000 |
| 438 | 1567.000000 | 54.631236 | 34.142202 | 0.000000 | 36.252650 | 49.009900 | 66.666700 | 851.612900 |
| 439 | 1567.000000 | 70.553777 | 38.434563 | 0.000000 | 48.046950 | 65.419600 | 84.944500 | 657.762100 |
| 440 | 1567.000000 | 11.511905 | 6.179258 | 0.000000 | 5.351100 | 12.075400 | 15.795850 | 33.058000 |
| 441 | 1567.000000 | 0.801569 | 0.185265 | 0.000000 | 0.679600 | 0.807600 | 0.927600 | 1.277100 |
| 442 | 1567.000000 | 1.344400 | 0.659860 | 0.000000 | 0.896500 | 1.262900 | 1.577550 | 5.131700 |
| 443 | 1567.000000 | 0.633537 | 0.144397 | 0.000000 | 0.550500 | 0.643500 | 0.733250 | 1.085100 |
| 444 | 1567.000000 | 0.894472 | 0.157108 | 0.000000 | 0.804800 | 0.902100 | 0.988800 | 1.351100 |
| 445 | 1567.000000 | 0.646677 | 0.142150 | 0.000000 | 0.555800 | 0.651100 | 0.748400 | 1.108700 |
| 446 | 1567.000000 | 1.174253 | 0.178586 | 0.000000 | 1.046800 | 1.163800 | 1.272300 | 1.763900 |
| 447 | 1567.000000 | 0.281715 | 0.086726 | 0.000000 | 0.226000 | 0.279700 | 0.338650 | 0.508500 |
| 448 | 1567.000000 | 0.332058 | 0.236349 | 0.000000 | 0.187700 | 0.251200 | 0.351100 | 1.475400 |
| 449 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 450 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 451 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 452 | 1567.000000 | 5.343403 | 0.928777 | 0.000000 | 4.762600 | 5.271400 | 5.912900 | 13.977600 |
| 453 | 1567.000000 | 5.457486 | 2.254311 | 0.000000 | 3.745150 | 5.227000 | 6.898750 | 34.490200 |
| 454 | 1567.000000 | 7.878710 | 3.065160 | 0.000000 | 5.803050 | 7.421900 | 9.576750 | 42.070300 |
| 455 | 1567.000000 | 3.634313 | 0.942560 | 0.000000 | 2.899100 | 3.722700 | 4.341750 | 10.184000 |
| 456 | 1567.000000 | 12.317820 | 8.129246 | 0.000000 | 8.815500 | 11.339500 | 14.387400 | 232.125800 |
| 457 | 1567.000000 | 5.260307 | 4.538236 | 0.000000 | 3.825250 | 4.791200 | 6.089400 | 164.109300 |
| 458 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 459 | 1567.000000 | 2.836569 | 1.347056 | 0.000000 | 2.290100 | 2.829800 | 3.308950 | 47.777200 |
| 460 | 1567.000000 | 29.178781 | 13.351320 | 0.000000 | 20.200100 | 26.164400 | 35.268400 | 149.385100 |
| 461 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 462 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 463 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 464 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 465 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 466 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 467 | 1567.000000 | 6.236131 | 8.668385 | 0.000000 | 4.697500 | 5.643400 | 6.386900 | 109.007400 |
| 468 | 1567.000000 | 223.171636 | 230.735685 | 0.000000 | 37.752950 | 148.440700 | 334.674000 | 999.877000 |
| 469 | 1567.000000 | 5.640612 | 3.165032 | 0.000000 | 4.836750 | 5.469400 | 6.003200 | 77.800700 |
| 470 | 1567.000000 | 5.347199 | 4.984854 | 0.000000 | 2.810900 | 4.055500 | 6.991150 | 87.134700 |
| 471 | 1567.000000 | 9.601890 | 10.172053 | 0.000000 | 5.792100 | 7.379000 | 9.707900 | 212.655700 |
| 472 | 1567.000000 | 137.272440 | 48.472081 | 0.000000 | 105.073150 | 137.853400 | 168.270250 | 492.771800 |
| 473 | 1567.000000 | 39.250722 | 22.560688 | 0.000000 | 24.785950 | 34.133700 | 47.690150 | 358.950400 |
| 474 | 1567.000000 | 37.468920 | 24.894309 | 0.000000 | 23.058250 | 32.657700 | 45.160350 | 415.435500 |
| 475 | 1567.000000 | 4.246252 | 2.619438 | 0.000000 | 3.473250 | 4.275300 | 4.741050 | 79.116200 |
| 476 | 1567.000000 | 20.055069 | 14.962725 | 0.000000 | 11.560500 | 15.941900 | 23.682400 | 274.887100 |
| 477 | 1567.000000 | 6.233960 | 10.172845 | 0.000000 | 4.087350 | 5.229300 | 6.699750 | 289.826400 |
| 478 | 1567.000000 | 0.127632 | 5.052374 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 200.000000 |
| 479 | 1567.000000 | 3.270822 | 2.641349 | 0.000000 | 2.621200 | 3.183300 | 3.624550 | 63.333600 |
| 480 | 1567.000000 | 75.248898 | 35.987799 | 0.000000 | 52.560300 | 70.284900 | 92.911650 | 221.974700 |
| 481 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 482 | 1567.000000 | 313.541586 | 281.579849 | 0.000000 | 0.000000 | 288.142600 | 512.390750 | 999.413500 |
| 483 | 1567.000000 | 203.400481 | 193.055768 | 0.000000 | 78.187650 | 145.331800 | 260.079000 | 989.473700 |
| 484 | 1567.000000 | 211.991606 | 213.134421 | 0.000000 | 73.903500 | 136.310200 | 288.918450 | 996.858600 |
| 485 | 1567.000000 | 198.031523 | 218.409558 | 0.000000 | 46.756400 | 110.057500 | 283.289000 | 994.000000 |
| 486 | 1567.000000 | 297.873034 | 287.564803 | 0.000000 | 0.000000 | 243.158900 | 497.384500 | 999.491100 |
| 487 | 1567.000000 | 235.787855 | 263.455453 | 0.000000 | 49.532400 | 109.976500 | 391.277500 | 995.744700 |
| 488 | 1567.000000 | 347.215842 | 253.828400 | 0.000000 | 124.104650 | 345.549700 | 507.497050 | 997.518600 |
| 489 | 1567.000000 | 268.001186 | 228.749130 | 0.000000 | 107.669300 | 216.574600 | 372.341900 | 994.003500 |
| 490 | 1567.000000 | 51.321273 | 18.089427 | 0.000000 | 38.381050 | 48.557100 | 61.489950 | 142.843600 |
| 491 | 1567.000000 | 2.423967 | 1.238045 | 0.000000 | 1.739000 | 2.244400 | 2.830000 | 12.769800 |
| 492 | 1567.000000 | 1.178451 | 2.947924 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 21.044300 |
| 493 | 1567.000000 | 2.530046 | 0.973948 | 0.833000 | 1.663750 | 2.529100 | 3.199100 | 9.402400 |
| 494 | 1567.000000 | 0.956442 | 6.615200 | 0.034200 | 0.139000 | 0.232500 | 0.563000 | 127.572800 |
| 495 | 1567.000000 | 6.807826 | 3.260019 | 1.772000 | 5.274600 | 6.607900 | 7.897200 | 107.692600 |
| 496 | 1567.000000 | 28.893873 | 24.790786 | 0.000000 | 15.912400 | 21.240100 | 31.961500 | 219.643600 |
| 497 | 1567.000000 | 11.436300 | 5.307630 | 0.000000 | 7.860800 | 10.701300 | 14.337300 | 40.281800 |
| 498 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 499 | 1567.000000 | 262.859941 | 324.699975 | 0.000000 | 0.000000 | 0.000000 | 536.122600 | 1000.000000 |
| 500 | 1567.000000 | 240.673807 | 322.911797 | 0.000000 | 0.000000 | 0.000000 | 505.225750 | 999.233700 |
| 501 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 502 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 503 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 504 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 505 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 506 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 507 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 508 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 509 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 510 | 1567.000000 | 55.692336 | 37.720271 | 0.000000 | 35.307100 | 46.975100 | 64.228450 | 451.485100 |
| 511 | 1567.000000 | 275.627217 | 329.601505 | 0.000000 | 0.000000 | 0.000000 | 554.010700 | 1000.000000 |
| 512 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 513 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 514 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 515 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 516 | 1567.000000 | 0.237853 | 6.387470 | 0.000000 | 0.000000 | 0.000000 | 0.130300 | 252.860400 |
| 517 | 1567.000000 | 0.609226 | 3.009759 | 0.000000 | 0.000000 | 0.000000 | 0.927550 | 113.275800 |
| 518 | 1567.000000 | 0.632829 | 2.919850 | 0.000000 | 0.000000 | 0.000000 | 1.240400 | 111.349500 |
| 519 | 1567.000000 | 6.376918 | 13.040544 | 0.000000 | 0.000000 | 3.255300 | 6.468900 | 184.348800 |
| 520 | 1567.000000 | 2.695999 | 5.702366 | 0.312100 | 1.552150 | 2.221000 | 2.903700 | 111.736500 |
| 521 | 1567.000000 | 11.610080 | 103.122996 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1000.000000 |
| 522 | 1567.000000 | 14.728866 | 7.104435 | 2.681100 | 10.182800 | 13.742600 | 17.808950 | 137.983800 |
| 523 | 1567.000000 | 0.453896 | 4.147581 | 0.025800 | 0.073050 | 0.100000 | 0.133200 | 111.333000 |
| 524 | 1567.000000 | 5.687782 | 20.663414 | 1.310400 | 3.769650 | 4.877100 | 6.450650 | 818.000500 |
| 525 | 1567.000000 | 5.475235 | 3.949726 | 0.000000 | 4.053900 | 5.107000 | 6.301850 | 80.040600 |
| 526 | 1567.000000 | 1.443457 | 0.958428 | 0.170500 | 0.484200 | 1.550100 | 2.211650 | 8.203700 |
| 527 | 1567.000000 | 6.395717 | 1.888698 | 2.170000 | 4.895450 | 6.410800 | 7.594250 | 14.447900 |
| 528 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 529 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 530 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 531 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 532 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 533 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 534 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 535 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 536 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 537 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 538 | 1567.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 539 | 1567.000000 | 3.018744 | 1.268292 | 0.000000 | 1.861500 | 3.018500 | 3.941800 | 6.580300 |
| 540 | 1567.000000 | 1.932909 | 0.743079 | 0.000000 | 1.369800 | 1.785300 | 2.454500 | 4.082500 |
| 541 | 1567.000000 | 9.562558 | 2.969120 | 0.000000 | 7.487300 | 9.459300 | 11.200850 | 25.779200 |
| 542 | 1567.000000 | 0.111066 | 0.004822 | 0.000000 | 0.109600 | 0.109600 | 0.113400 | 0.118400 |
| 543 | 1567.000000 | 0.008460 | 0.001562 | 0.000000 | 0.007800 | 0.007800 | 0.009000 | 0.024000 |
| 544 | 1567.000000 | 0.002506 | 0.000309 | 0.000000 | 0.002400 | 0.002600 | 0.002600 | 0.004700 |
| 545 | 1567.000000 | 7.601689 | 1.342513 | 0.000000 | 7.116000 | 7.116000 | 8.008950 | 21.044300 |
| 546 | 1567.000000 | 0.867133 | 0.525275 | 0.000000 | 0.619500 | 0.827300 | 1.216500 | 3.978600 |
| 547 | 1567.000000 | 336.589181 | 150.242733 | 0.000000 | 398.575000 | 401.344000 | 406.763000 | 421.702000 |
| 548 | 1567.000000 | 63.122905 | 28.332409 | 0.000000 | 72.590000 | 73.546000 | 76.960000 | 83.720000 |
| 549 | 1567.000000 | 0.553208 | 0.662599 | 0.000000 | 0.175400 | 0.380800 | 0.773400 | 7.065600 |
| 550 | 1567.000000 | 14.190428 | 7.788334 | 0.000000 | 13.415000 | 15.910000 | 18.405000 | 131.680000 |
| 551 | 1567.000000 | 1.026509 | 1.324688 | 0.000000 | 0.670000 | 1.020000 | 1.330000 | 39.330000 |
| 552 | 1567.000000 | 0.230779 | 0.272464 | 0.000000 | 0.065800 | 0.160600 | 0.321750 | 2.718200 |
| 553 | 1567.000000 | 6.425630 | 3.496892 | 0.000000 | 6.070750 | 7.094100 | 8.316650 | 56.930300 |
| 554 | 1567.000000 | 0.420090 | 0.578109 | 0.000000 | 0.273350 | 0.417200 | 0.533550 | 17.478100 |
| 555 | 1567.000000 | 48.165108 | 38.672384 | 0.000000 | 21.344000 | 45.838000 | 69.630650 | 303.550000 |
| 556 | 1567.000000 | 3.517227 | 1.956756 | 0.000000 | 3.318350 | 3.926300 | 4.564950 | 35.319800 |
| 557 | 1567.000000 | 1.353767 | 1.811760 | 0.000000 | 0.896550 | 1.360500 | 1.815600 | 54.291700 |
| 558 | 1567.000000 | 0.994374 | 0.087520 | 0.000000 | 0.955200 | 0.972700 | 1.000800 | 1.512100 |
| 559 | 1567.000000 | 0.325500 | 0.201496 | 0.000000 | 0.149700 | 0.290900 | 0.443600 | 1.073700 |
| 560 | 1567.000000 | 0.072397 | 0.051594 | 0.000000 | 0.036200 | 0.059200 | 0.089000 | 0.445700 |
| 561 | 1567.000000 | 32.264353 | 19.037484 | 0.000000 | 15.740700 | 29.682200 | 44.113400 | 101.114600 |
| 562 | 1567.000000 | 216.957377 | 99.925253 | 0.000000 | 250.420000 | 264.272000 | 264.733000 | 311.404000 |
| 563 | 1567.000000 | 0.561235 | 0.280600 | 0.000000 | 0.567100 | 0.602300 | 0.738250 | 1.298800 |
| 564 | 1567.000000 | 5.322151 | 3.421456 | 0.000000 | 4.045000 | 4.980000 | 7.310000 | 32.580000 |
| 565 | 1567.000000 | 0.120242 | 0.092119 | 0.000000 | 0.087700 | 0.090300 | 0.166850 | 0.689200 |
| 566 | 1567.000000 | 2.156008 | 1.364539 | 0.000000 | 1.658750 | 2.090200 | 2.909150 | 14.014100 |
| 567 | 1567.000000 | 0.049618 | 0.037496 | 0.000000 | 0.036600 | 0.038200 | 0.068100 | 0.293200 |
| 568 | 1567.000000 | 2.025161 | 1.298442 | 0.000000 | 1.549000 | 1.884400 | 2.807750 | 12.746200 |
| 569 | 1567.000000 | 17.438590 | 12.260744 | 0.000000 | 12.593550 | 15.466200 | 23.035200 | 84.802400 |
| 570 | 1567.000000 | 530.523623 | 17.499736 | 317.196400 | 530.702700 | 532.398200 | 534.356400 | 589.508200 |
| 571 | 1567.000000 | 2.101836 | 0.275112 | 0.980200 | 1.982900 | 2.118600 | 2.290650 | 2.739500 |
| 572 | 1567.000000 | 28.450165 | 86.304681 | 3.540000 | 7.500000 | 8.650000 | 10.130000 | 454.560000 |
| 573 | 1567.000000 | 0.345636 | 0.248478 | 0.066700 | 0.242250 | 0.293400 | 0.366900 | 2.196700 |
| 574 | 1567.000000 | 9.162315 | 26.920150 | 1.039500 | 2.567850 | 2.975800 | 3.492500 | 170.020400 |
| 575 | 1567.000000 | 0.104729 | 0.067791 | 0.023000 | 0.075100 | 0.089500 | 0.112150 | 0.550200 |
| 576 | 1567.000000 | 5.563747 | 16.921369 | 0.663600 | 1.408450 | 1.624500 | 1.902000 | 90.423500 |
| 577 | 1567.000000 | 16.642363 | 12.485267 | 4.582000 | 11.501550 | 13.817900 | 17.080900 | 96.960100 |
| 578 | 1567.000000 | 0.008524 | 0.012879 | -0.016900 | 0.000000 | 0.000000 | 0.017350 | 0.102800 |
| 579 | 1567.000000 | 0.006637 | 0.010213 | 0.000000 | 0.000000 | 0.000000 | 0.012300 | 0.079900 |
| 580 | 1567.000000 | 0.002128 | 0.003284 | 0.000000 | 0.000000 | 0.000000 | 0.003900 | 0.028600 |
| 581 | 1567.000000 | 38.623767 | 72.871466 | 0.000000 | 0.000000 | 0.000000 | 57.449750 | 737.304800 |
| 582 | 1567.000000 | 0.499777 | 0.013084 | 0.000000 | 0.497900 | 0.500200 | 0.502350 | 0.509800 |
| 583 | 1567.000000 | 0.015308 | 0.017179 | 0.000000 | 0.011600 | 0.013800 | 0.016500 | 0.476600 |
| 584 | 1567.000000 | 0.003844 | 0.003721 | 0.000000 | 0.003100 | 0.003600 | 0.004100 | 0.104500 |
| 585 | 1567.000000 | 3.065869 | 3.577730 | 0.000000 | 2.306200 | 2.757600 | 3.294950 | 99.303200 |
| 586 | 1567.000000 | 0.021445 | 0.012366 | -0.016900 | 0.013400 | 0.020500 | 0.027600 | 0.102800 |
| 587 | 1567.000000 | 0.016464 | 0.008815 | 0.000000 | 0.010600 | 0.014800 | 0.020300 | 0.079900 |
| 588 | 1567.000000 | 0.005280 | 0.002869 | 0.000000 | 0.003300 | 0.004600 | 0.006400 | 0.028600 |
| 589 | 1567.000000 | 99.606461 | 93.895701 | 0.000000 | 44.368600 | 71.778000 | 114.749700 | 737.304800 |
| Pass/Fail | 1567.000000 | -0.867262 | 0.498010 | -1.000000 | -1.000000 | -1.000000 | -1.000000 | 1.000000 |
def boxhistplot(columns,data):
fig = px.histogram(data, x = data[column], color = 'Pass/Fail')
fig.show()
col = ['Time','0','1','2','3','586','587','588','589','23','24','67','90','139','140','161','162','204','225','296','297']
for column in col:
boxhistplot(column, data)
data1 = data.drop(columns = ['Time'], axis = 1)
data2 = data1.drop(columns = ['Pass/Fail'], axis = 1)
The Lucifer ML uses SMOTE (Oversampling) method before applying hyperparameter tuning.
import warnings
warnings.filterwarnings('ignore')
from luciferml.supervised.classification import Classification
X = data2
y = data1["Pass/Fail"]
classifier = Classification(
predictor='all',
params= {},
cv_folds=2,
epochs=5)
classifier.fit(X, y)
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Started LuciferML
Checking if labels or features are categorical! [*]
Features are not categorical [ ✓ ]
Labels are not categorical [ ✓ ]
Checking for Categorical Variables Done [ ✓ ]
Checking for Sparse Matrix [*]
Splitting Data into Train and Validation Sets [*]
Splitting Done [ ✓ ]
Scaling Training and Test Sets [*]
Scaling Done [ ✓ ]
Training All Classifiers [*]
[17:34:15] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:573:
Parameters: { "verbose" } might not be used.
This may not be accurate due to some parameters are only used in language bindings but
passed down to XGBoost core. Or some parameters are not used but slip through this
verification. Please open an issue if you find above cases.
[17:34:15] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:1095: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.
[17:34:19] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:573:
Parameters: { "verbose" } might not be used.
This may not be accurate due to some parameters are only used in language bindings but
passed down to XGBoost core. Or some parameters are not used but slip through this
verification. Please open an issue if you find above cases.
[17:34:19] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:1095: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.
[17:34:20] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:573:
Parameters: { "verbose" } might not be used.
This may not be accurate due to some parameters are only used in language bindings but
passed down to XGBoost core. Or some parameters are not used but slip through this
verification. Please open an issue if you find above cases.
[17:34:20] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:1095: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.
Epoch 1/5
20/20 [==============================] - 0s 2ms/step - loss: 0.5835 - accuracy: 0.9361
Epoch 2/5
20/20 [==============================] - 0s 2ms/step - loss: 0.4620 - accuracy: 0.9361
Epoch 3/5
20/20 [==============================] - 0s 1ms/step - loss: 0.3484 - accuracy: 0.9361
Epoch 4/5
20/20 [==============================] - 0s 1ms/step - loss: 0.2655 - accuracy: 0.9361
Epoch 5/5
20/20 [==============================] - 0s 1ms/step - loss: 0.2148 - accuracy: 0.9361
Epoch 1/5
20/20 [==============================] - 1s 2ms/step - loss: 0.6509 - accuracy: 0.6874
Epoch 2/5
20/20 [==============================] - 0s 2ms/step - loss: 0.5253 - accuracy: 0.8963
Epoch 3/5
20/20 [==============================] - 0s 1ms/step - loss: 0.4079 - accuracy: 0.9362
Epoch 4/5
20/20 [==============================] - 0s 1ms/step - loss: 0.3153 - accuracy: 0.9362
Epoch 5/5
20/20 [==============================] - 0s 1ms/step - loss: 0.2514 - accuracy: 0.9362
| Accuracy | KFold Accuracy | |
|---|---|---|
| Logistic Regression | 86.942675 | 89.385150 |
| Stochastic Gradient Descent | 90.127389 | 90.342852 |
| Perceptron | 86.624204 | 86.592935 |
| Passive Aggressive Classifier | 86.305732 | 84.277660 |
| Ridge Classifier | 91.082803 | 90.342342 |
| Support Vector Machine | 92.356688 | 93.615319 |
| K-Nearest Neighbours | 91.401274 | 93.455830 |
| Decision Trees | 85.987261 | 88.428212 |
| Naive Bayes | 18.789809 | 26.016301 |
| Random Forest Classifier | 92.038217 | 93.615319 |
| Gradient Boosting Classifier | 90.445860 | 92.976469 |
| AdaBoost Classifier | 91.082803 | 92.099403 |
| Bagging Classifier | 91.719745 | 92.896851 |
| Extra Trees Classifier | 92.038217 | 93.296340 |
| LightGBM Classifier | 92.356688 | 93.615319 |
| CatBoost Classifier | 92.356688 | 93.615319 |
| XGBoost Classifier | 92.038217 | 93.615447 |
| Artificial Neural Network | 0.000000 | 93.615319 |
Complete [ ✓ ] Time Elapsed : 348.75034284591675 seconds
CatBoost Classifier has highest
from sklearn.preprocessing import normalize
X = data2
y = data1['Pass/Fail']
X = X.dropna(thresh=30)
X = X.fillna(method='backfill')
X = normalize(X)
X = X[(np.max(X, axis=1) - np.min(X, axis=1)) / np.min(X, axis=1) < 10**2, :]
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4)
from sklearn.linear_model import LinearRegression
clf = LinearRegression()
clf.fit(X_train, y_train)
y_test_hat = clf.predict(X_test)
from sklearn.metrics import median_absolute_error
median_absolute_error(y_test_hat, y_test)
median_absolute_error(clf.predict(X_train), y_train)
0.16569028329564334
from sklearn.model_selection import KFold
kf = KFold(n_splits=4)
scores = []
for train_index, test_index in kf.split(X):
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
scores.append(
median_absolute_error(clf.fit(X_train, y_train).predict(X_test), y_test)
)
np.mean(scores)
0.4070495389618295
from sklearn.model_selection import RepeatedKFold
rkf = RepeatedKFold(n_splits=4, n_repeats=2)
scores = []
for train_index, test_index in rkf.split(X):
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
scores.append(
median_absolute_error(clf.fit(X_train, y_train).predict(X_test), y_test)
)
np.mean(scores)
0.29472798188673166
from sklearn.model_selection import LeaveOneOut
loo = LeaveOneOut()
scores = []
for train_index, test_index in loo.split(X):
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
scores.append(
median_absolute_error(clf.fit(X_train, y_train).predict(X_test), y_test)
)
scores = np.array(scores)
np.mean(scores)
41.91986024237037
from sklearn.model_selection import StratifiedKFold
skf = StratifiedKFold(n_splits=4)
scores = []
t = (np.random.random(size=100) > 0.1).astype(int)[:, np.newaxis]
for train_index, test_index in skf.split(
np.sort((np.random.random(size=100) > 0.1)).astype(int),
np.sort(np.random.random(size=100) > 0.1).astype(int)
):
X_train, X_test = t[train_index], t[test_index]
y_train, y_test = t[train_index], t[test_index]
scores.append(
median_absolute_error(clf.fit(X_train, y_train).predict(X_test), y_test)
)
scores = np.array(scores)
np.mean(scores)
0.0
from sklearn import metrics
from sklearn.metrics import recall_score
from imblearn.over_sampling import SMOTE
from sklearn.model_selection import train_test_split
X = data2
y = data1['Pass/Fail']
test_size = 0.30
seed = 7
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=seed)
type(X_train)
print("Before UpSampling, counts of label '1': {}".format(sum(y_train==1)))
print("Before UpSampling, counts of label '0': {} \n".format(sum(y_train==0)))
sm = SMOTE(sampling_strategy = 1 ,k_neighbors = 5, random_state=1)
X_train_res, y_train_res = sm.fit_resample(X_train, y_train.ravel())
print("After UpSampling, counts of label '1': {}".format(sum(y_train_res==1)))
print("After UpSampling, counts of label '0': {} \n".format(sum(y_train_res==0)))
print('After UpSampling, the shape of train_X: {}'.format(X_train_res.shape))
print('After UpSampling, the shape of train_y: {} \n'.format(y_train_res.shape))
Before UpSampling, counts of label '1': 81 Before UpSampling, counts of label '0': 0 After UpSampling, counts of label '1': 1015 After UpSampling, counts of label '0': 0 After UpSampling, the shape of train_X: (2030, 590) After UpSampling, the shape of train_y: (2030,)
from sklearn.linear_model import LogisticRegression
model = LogisticRegression()
model.fit(X_train, y_train)
y_predict = model.predict(X_test)
model_score = model.score(X_test, y_test)
print(model_score)
0.9426751592356688
test_pred = model.predict(X_test)
print(metrics.classification_report(y_test, test_pred))
print(metrics.confusion_matrix(y_test, test_pred))
precision recall f1-score support
-1 0.95 0.99 0.97 448
1 0.00 0.00 0.00 23
accuracy 0.94 471
macro avg 0.48 0.50 0.49 471
weighted avg 0.90 0.94 0.92 471
[[444 4]
[ 23 0]]
model.fit(X_train_res, y_train_res)
y_predict = model.predict(X_test)
model_score = model.score(X_test, y_test)
print(model_score)
print(metrics.confusion_matrix(y_test, y_predict))
print(metrics.classification_report(y_test, y_predict))
0.6518046709129511
[[292 156]
[ 8 15]]
precision recall f1-score support
-1 0.97 0.65 0.78 448
1 0.09 0.65 0.15 23
accuracy 0.65 471
macro avg 0.53 0.65 0.47 471
weighted avg 0.93 0.65 0.75 471
from imblearn.over_sampling import RandomOverSampler
ros = RandomOverSampler()
X_ros, y_ros = ros.fit_resample(X_train, y_train)
y_ros.shape
(2030,)
X_ros.shape
(2030, 590)
df_resampled, y_resampled = ros.fit_resample(X_train, y_train)
df_resampled.head()
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ... | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2992.40 | 2467.07 | 2191.6667 | 1107.4330 | 1.3529 | 100.0 | 103.4233 | 0.1206 | 1.4993 | -0.0091 | ... | 0.0062 | 192.2985 | 0.4996 | 0.0326 | 0.0065 | 6.5274 | 0.0095 | 0.0184 | 0.0062 | 192.2985 |
| 1 | 3009.65 | 2515.97 | 2216.4778 | 1242.2350 | 0.8379 | 100.0 | 105.1111 | 0.1233 | 1.5996 | -0.0095 | ... | 0.0000 | 0.0000 | 0.5029 | 0.0198 | 0.0042 | 3.9426 | 0.0142 | 0.0102 | 0.0031 | 71.7780 |
| 2 | 3034.90 | 2598.02 | 2208.2334 | 1517.0152 | 1.0980 | 100.0 | 110.1900 | 0.1247 | 1.4119 | -0.0031 | ... | 0.0000 | 0.0000 | 0.5052 | 0.0168 | 0.0044 | 3.3338 | 0.0279 | 0.0217 | 0.0061 | 77.7519 |
| 3 | 2923.19 | 2516.40 | 2180.8889 | 1084.7221 | 0.9085 | 100.0 | 94.2467 | 0.1226 | 1.3137 | 0.0345 | ... | 0.0000 | 0.0000 | 0.4939 | 0.0163 | 0.0037 | 3.2914 | 0.0166 | 0.0122 | 0.0036 | 73.6335 |
| 4 | 2927.71 | 2525.39 | 2199.6556 | 1140.3983 | 1.3369 | 100.0 | 103.0967 | 0.1227 | 1.4052 | -0.0157 | ... | 0.0000 | 0.0000 | 0.5055 | 0.0195 | 0.0048 | 3.8618 | 0.0184 | 0.0148 | 0.0054 | 80.1759 |
5 rows × 590 columns
y_resampled.head()
0 1 1 -1 2 -1 3 -1 4 -1 Name: Pass/Fail, dtype: int64
frames = [df_resampled, y_resampled]
result = pd.concat(frames)
result.to_csv('OS.csv', index=False)
data3 = pd.read_csv('OS.csv')
data4 = data3.drop(columns = ['C591'], axis = 1)
X = data4
y = data3["C591"]
classifier = Classification(
predictor='all',
params= {},
cv_folds=2,
epochs=5)
classifier.fit(X, y)
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Started LuciferML
Checking if labels or features are categorical! [*]
Features are not categorical [ ✓ ]
Labels are not categorical [ ✓ ]
Checking for Categorical Variables Done [ ✓ ]
Checking for Sparse Matrix [*]
Splitting Data into Train and Validation Sets [*]
Splitting Done [ ✓ ]
Scaling Training and Test Sets [*]
Scaling Done [ ✓ ]
Training All Classifiers [*]
[19:55:15] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:573:
Parameters: { "verbose" } might not be used.
This may not be accurate due to some parameters are only used in language bindings but
passed down to XGBoost core. Or some parameters are not used but slip through this
verification. Please open an issue if you find above cases.
[19:55:15] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:1095: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.
[19:55:19] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:573:
Parameters: { "verbose" } might not be used.
This may not be accurate due to some parameters are only used in language bindings but
passed down to XGBoost core. Or some parameters are not used but slip through this
verification. Please open an issue if you find above cases.
[19:55:19] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:1095: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.
[19:55:20] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:573:
Parameters: { "verbose" } might not be used.
This may not be accurate due to some parameters are only used in language bindings but
passed down to XGBoost core. Or some parameters are not used but slip through this
verification. Please open an issue if you find above cases.
[19:55:20] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:1095: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.
Epoch 1/5
26/26 [==============================] - 1s 3ms/step - loss: 0.8079 - accuracy: 0.5333
Epoch 2/5
26/26 [==============================] - 0s 3ms/step - loss: 0.6444 - accuracy: 0.6872
Epoch 3/5
26/26 [==============================] - 0s 4ms/step - loss: 0.5778 - accuracy: 0.7611
Epoch 4/5
26/26 [==============================] - 0s 4ms/step - loss: 0.5304 - accuracy: 0.7956
Epoch 5/5
26/26 [==============================] - 0s 4ms/step - loss: 0.4919 - accuracy: 0.8337
Epoch 1/5
26/26 [==============================] - 1s 3ms/step - loss: 0.6807 - accuracy: 0.5739
Epoch 2/5
26/26 [==============================] - 0s 3ms/step - loss: 0.6424 - accuracy: 0.7032
Epoch 3/5
26/26 [==============================] - 0s 4ms/step - loss: 0.5903 - accuracy: 0.7414
Epoch 4/5
26/26 [==============================] - 0s 4ms/step - loss: 0.5222 - accuracy: 0.7734
Epoch 5/5
26/26 [==============================] - 0s 4ms/step - loss: 0.4455 - accuracy: 0.8005
| Accuracy | KFold Accuracy | |
|---|---|---|
| Logistic Regression | 94.581281 | 90.763547 |
| Stochastic Gradient Descent | 89.655172 | 90.332512 |
| Perceptron | 92.364532 | 87.684729 |
| Passive Aggressive Classifier | 94.334975 | 90.763547 |
| Ridge Classifier | 92.118227 | 87.438424 |
| Support Vector Machine | 99.014778 | 95.874384 |
| K-Nearest Neighbours | 92.610837 | 81.280788 |
| Decision Trees | 97.783251 | 93.780788 |
| Naive Bayes | 58.374384 | 61.330049 |
| Random Forest Classifier | 100.000000 | 99.507389 |
| Gradient Boosting Classifier | 99.507389 | 97.167488 |
| AdaBoost Classifier | 94.581281 | 92.118227 |
| Bagging Classifier | 99.014778 | 97.721675 |
| Extra Trees Classifier | 100.000000 | 100.000000 |
| LightGBM Classifier | 99.753695 | 98.522167 |
| CatBoost Classifier | 100.000000 | 98.583744 |
| XGBoost Classifier | 100.000000 | 98.152709 |
| Artificial Neural Network | 0.000000 | 77.216749 |
Complete [ ✓ ] Time Elapsed : 461.3896508216858 seconds
from imblearn.under_sampling import ClusterCentroids
cc = ClusterCentroids()
X_cc, y_cc = cc.fit_resample(X_train, y_train)
X_cc.shape
(162, 590)
y_cc
0 -1
1 -1
2 -1
3 -1
4 -1
..
157 1
158 1
159 1
160 1
161 1
Name: Pass/Fail, Length: 162, dtype: int64
df_resampled2, y_resampled2 = cc.fit_resample(X_train, y_train)
df_resampled2.shape
(162, 590)
y_resampled2.shape
(162,)
frames2 = [df_resampled2, y_resampled2]
result2 = pd.concat(frames2)
result2.to_csv('US.csv', index=False)
data5 = pd.read_csv('US.csv')
data6 = data5.drop(columns = ['C591'], axis = 1)
X = data6
y = data5["C591"]
classifier = Classification(
predictor='cat',
params= {},
cv_folds=2,
epochs=5)
classifier.fit(X, y)
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Started LuciferML
Checking if labels or features are categorical! [*]
Features are not categorical [ ✓ ]
Labels are not categorical [ ✓ ]
Checking for Categorical Variables Done [ ✓ ]
Checking for Sparse Matrix [*]
Splitting Data into Train and Validation Sets [*]
Splitting Done [ ✓ ]
Scaling Training and Test Sets [*]
Scaling Done [ ✓ ]
Training CatBoostClassifier on Training Set [*]
Model Training Done [ ✓ ]
Predicting Data [*]
Data Prediction Done [ ✓ ]
Making Confusion Matrix [*]
[[15 2]
[ 1 15]]
Confusion Matrix Done [ ✓ ] Evaluating Model Performance [*] Validation Accuracy is : 0.9090909090909091 Evaluating Model Performance [ ✓ ] Applying K-Fold Cross Validation [*] Accuracy: 81.42 % Standard Deviation: 2.96 % K-Fold Cross Validation [ ✓ ] Complete [ ✓ ] Time Elapsed : 40.78955698013306 seconds
import h2o
h2o.init()
Checking whether there is an H2O instance running at http://localhost:54321 . connected.
| H2O_cluster_uptime: | 6 hours 20 mins |
| H2O_cluster_timezone: | Asia/Kolkata |
| H2O_data_parsing_timezone: | UTC |
| H2O_cluster_version: | 3.34.0.3 |
| H2O_cluster_version_age: | 1 month and 29 days |
| H2O_cluster_name: | H2O_from_python_Admin_ggq0m8 |
| H2O_cluster_total_nodes: | 1 |
| H2O_cluster_free_memory: | 1.356 Gb |
| H2O_cluster_total_cores: | 8 |
| H2O_cluster_allowed_cores: | 8 |
| H2O_cluster_status: | locked, healthy |
| H2O_connection_url: | http://localhost:54321 |
| H2O_connection_proxy: | {"http": null, "https": null} |
| H2O_internal_security: | False |
| H2O_API_Extensions: | Amazon S3, Algos, AutoML, Core V3, TargetEncoder, Core V4 |
| Python_version: | 3.8.8 final |
from h2o.estimators.pca import H2OPrincipalComponentAnalysisEstimator
df = h2o.import_file("C:\\Users\\Admin\\Desktop\\FMT\\signal-data1.csv")
df.pca = H2OPrincipalComponentAnalysisEstimator(k=50)
response = "C591"
fm = df.col_names
fm.remove(response)
Parse progress: |████████████████████████████████████████████████████████████████| (done) 100%
df.pca.train(x=fm, training_frame=df)
pca Model Build progress: |██████████████████████████████████████████████████████| (done) 100% Model Details ============= H2OPrincipalComponentAnalysisEstimator : Principal Components Analysis Model Key: PCA_model_python_1638771670270_5 Importance of components:
| pc1 | pc2 | pc3 | pc4 | pc5 | pc6 | pc7 | pc8 | pc9 | ... | pc41 | pc42 | pc43 | pc44 | pc45 | pc46 | pc47 | pc48 | pc49 | pc50 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Standard deviation | 15109.664970 | 6725.342943 | 4413.131230 | 2870.264991 | 1498.195772 | 1174.226423 | 1069.430682 | 683.967834 | 539.561631 | ... | 105.901247 | 103.321398 | 102.225876 | 98.041429 | 92.402485 | 89.151358 | 84.137627 | 72.015635 | 70.179948 | 68.303435 |
| 1 | Proportion of Variance | 0.737682 | 0.146146 | 0.062929 | 0.026620 | 0.007253 | 0.004455 | 0.003695 | 0.001512 | 0.000941 | ... | 0.000036 | 0.000034 | 0.000034 | 0.000031 | 0.000028 | 0.000026 | 0.000023 | 0.000017 | 0.000016 | 0.000015 |
| 2 | Cumulative Proportion | 0.737682 | 0.883828 | 0.946757 | 0.973377 | 0.980630 | 0.985085 | 0.988780 | 0.990292 | 0.991233 | ... | 0.999621 | 0.999656 | 0.999690 | 0.999721 | 0.999748 | 0.999774 | 0.999797 | 0.999814 | 0.999829 | 0.999845 |
3 rows × 51 columns
ModelMetricsPCA: pca ** Reported on train data. ** MSE: NaN RMSE: NaN Scoring History for GramSVD:
| timestamp | duration | iterations | ||
|---|---|---|---|---|
| 0 | 2021-12-06 18:14:03 | 0.432 sec | 0.0 |
df
| C1 | C2 | C3 | C4 | C5 | C6 | C7 | C8 | C9 | C10 | C11 | C12 | C13 | C14 | C15 | C16 | C17 | C18 | C19 | C20 | C21 | C22 | C23 | C24 | C25 | C26 | C27 | C28 | C29 | C30 | C31 | C32 | C33 | C34 | C35 | C36 | C37 | C38 | C39 | C40 | C41 | C42 | C43 | C44 | C45 | C46 | C47 | C48 | C49 | C50 | C51 | C52 | C53 | C54 | C55 | C56 | C57 | C58 | C59 | C60 | C61 | C62 | C63 | C64 | C65 | C66 | C67 | C68 | C69 | C70 | C71 | C72 | C73 | C74 | C75 | C76 | C77 | C78 | C79 | C80 | C81 | C82 | C83 | C84 | C85 | C86 | C87 | C88 | C89 | C90 | C91 | C92 | C93 | C94 | C95 | C96 | C97 | C98 | C99 | C100 | C101 | C102 | C103 | C104 | C105 | C106 | C107 | C108 | C109 | C110 | C111 | C112 | C113 | C114 | C115 | C116 | C117 | C118 | C119 | C120 | C121 | C122 | C123 | C124 | C125 | C126 | C127 | C128 | C129 | C130 | C131 | C132 | C133 | C134 | C135 | C136 | C137 | C138 | C139 | C140 | C141 | C142 | C143 | C144 | C145 | C146 | C147 | C148 | C149 | C150 | C151 | C152 | C153 | C154 | C155 | C156 | C157 | C158 | C159 | C160 | C161 | C162 | C163 | C164 | C165 | C166 | C167 | C168 | C169 | C170 | C171 | C172 | C173 | C174 | C175 | C176 | C177 | C178 | C179 | C180 | C181 | C182 | C183 | C184 | C185 | C186 | C187 | C188 | C189 | C190 | C191 | C192 | C193 | C194 | C195 | C196 | C197 | C198 | C199 | C200 | C201 | C202 | C203 | C204 | C205 | C206 | C207 | C208 | C209 | C210 | C211 | C212 | C213 | C214 | C215 | C216 | C217 | C218 | C219 | C220 | C221 | C222 | C223 | C224 | C225 | C226 | C227 | C228 | C229 | C230 | C231 | C232 | C233 | C234 | C235 | C236 | C237 | C238 | C239 | C240 | C241 | C242 | C243 | C244 | C245 | C246 | C247 | C248 | C249 | C250 | C251 | C252 | C253 | C254 | C255 | C256 | C257 | C258 | C259 | C260 | C261 | C262 | C263 | C264 | C265 | C266 | C267 | C268 | C269 | C270 | C271 | C272 | C273 | C274 | C275 | C276 | C277 | C278 | C279 | C280 | C281 | C282 | C283 | C284 | C285 | C286 | C287 | C288 | C289 | C290 | C291 | C292 | C293 | C294 | C295 | C296 | C297 | C298 | C299 | C300 | C301 | C302 | C303 | C304 | C305 | C306 | C307 | C308 | C309 | C310 | C311 | C312 | C313 | C314 | C315 | C316 | C317 | C318 | C319 | C320 | C321 | C322 | C323 | C324 | C325 | C326 | C327 | C328 | C329 | C330 | C331 | C332 | C333 | C334 | C335 | C336 | C337 | C338 | C339 | C340 | C341 | C342 | C343 | C344 | C345 | C346 | C347 | C348 | C349 | C350 | C351 | C352 | C353 | C354 | C355 | C356 | C357 | C358 | C359 | C360 | C361 | C362 | C363 | C364 | C365 | C366 | C367 | C368 | C369 | C370 | C371 | C372 | C373 | C374 | C375 | C376 | C377 | C378 | C379 | C380 | C381 | C382 | C383 | C384 | C385 | C386 | C387 | C388 | C389 | C390 | C391 | C392 | C393 | C394 | C395 | C396 | C397 | C398 | C399 | C400 | C401 | C402 | C403 | C404 | C405 | C406 | C407 | C408 | C409 | C410 | C411 | C412 | C413 | C414 | C415 | C416 | C417 | C418 | C419 | C420 | C421 | C422 | C423 | C424 | C425 | C426 | C427 | C428 | C429 | C430 | C431 | C432 | C433 | C434 | C435 | C436 | C437 | C438 | C439 | C440 | C441 | C442 | C443 | C444 | C445 | C446 | C447 | C448 | C449 | C450 | C451 | C452 | C453 | C454 | C455 | C456 | C457 | C458 | C459 | C460 | C461 | C462 | C463 | C464 | C465 | C466 | C467 | C468 | C469 | C470 | C471 | C472 | C473 | C474 | C475 | C476 | C477 | C478 | C479 | C480 | C481 | C482 | C483 | C484 | C485 | C486 | C487 | C488 | C489 | C490 | C491 | C492 | C493 | C494 | C495 | C496 | C497 | C498 | C499 | C500 | C501 | C502 | C503 | C504 | C505 | C506 | C507 | C508 | C509 | C510 | C511 | C512 | C513 | C514 | C515 | C516 | C517 | C518 | C519 | C520 | C521 | C522 | C523 | C524 | C525 | C526 | C527 | C528 | C529 | C530 | C531 | C532 | C533 | C534 | C535 | C536 | C537 | C538 | C539 | C540 | C541 | C542 | C543 | C544 | C545 | C546 | C547 | C548 | C549 | C550 | C551 | C552 | C553 | C554 | C555 | C556 | C557 | C558 | C559 | C560 | C561 | C562 | C563 | C564 | C565 | C566 | C567 | C568 | C569 | C570 | C571 | C572 | C573 | C574 | C575 | C576 | C577 | C578 | C579 | C580 | C581 | C582 | C583 | C584 | C585 | C586 | C587 | C588 | C589 | C590 | C591 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 | 100 | 101 | 102 | 103 | 104 | 105 | 106 | 107 | 108 | 109 | 110 | 111 | 112 | 113 | 114 | 115 | 116 | 117 | 118 | 119 | 120 | 121 | 122 | 123 | 124 | 125 | 126 | 127 | 128 | 129 | 130 | 131 | 132 | 133 | 134 | 135 | 136 | 137 | 138 | 139 | 140 | 141 | 142 | 143 | 144 | 145 | 146 | 147 | 148 | 149 | 150 | 151 | 152 | 153 | 154 | 155 | 156 | 157 | 158 | 159 | 160 | 161 | 162 | 163 | 164 | 165 | 166 | 167 | 168 | 169 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | 179 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | 187 | 188 | 189 | 190 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | 200 | 201 | 202 | 203 | 204 | 205 | 206 | 207 | 208 | 209 | 210 | 211 | 212 | 213 | 214 | 215 | 216 | 217 | 218 | 219 | 220 | 221 | 222 | 223 | 224 | 225 | 226 | 227 | 228 | 229 | 230 | 231 | 232 | 233 | 234 | 235 | 236 | 237 | 238 | 239 | 240 | 241 | 242 | 243 | 244 | 245 | 246 | 247 | 248 | 249 | 250 | 251 | 252 | 253 | 254 | 255 | 256 | 257 | 258 | 259 | 260 | 261 | 262 | 263 | 264 | 265 | 266 | 267 | 268 | 269 | 270 | 271 | 272 | 273 | 274 | 275 | 276 | 277 | 278 | 279 | 280 | 281 | 282 | 283 | 284 | 285 | 286 | 287 | 288 | 289 | 290 | 291 | 292 | 293 | 294 | 295 | 296 | 297 | 298 | 299 | 300 | 301 | 302 | 303 | 304 | 305 | 306 | 307 | 308 | 309 | 310 | 311 | 312 | 313 | 314 | 315 | 316 | 317 | 318 | 319 | 320 | 321 | 322 | 323 | 324 | 325 | 326 | 327 | 328 | 329 | 330 | 331 | 332 | 333 | 334 | 335 | 336 | 337 | 338 | 339 | 340 | 341 | 342 | 343 | 344 | 345 | 346 | 347 | 348 | 349 | 350 | 351 | 352 | 353 | 354 | 355 | 356 | 357 | 358 | 359 | 360 | 361 | 362 | 363 | 364 | 365 | 366 | 367 | 368 | 369 | 370 | 371 | 372 | 373 | 374 | 375 | 376 | 377 | 378 | 379 | 380 | 381 | 382 | 383 | 384 | 385 | 386 | 387 | 388 | 389 | 390 | 391 | 392 | 393 | 394 | 395 | 396 | 397 | 398 | 399 | 400 | 401 | 402 | 403 | 404 | 405 | 406 | 407 | 408 | 409 | 410 | 411 | 412 | 413 | 414 | 415 | 416 | 417 | 418 | 419 | 420 | 421 | 422 | 423 | 424 | 425 | 426 | 427 | 428 | 429 | 430 | 431 | 432 | 433 | 434 | 435 | 436 | 437 | 438 | 439 | 440 | 441 | 442 | 443 | 444 | 445 | 446 | 447 | 448 | 449 | 450 | 451 | 452 | 453 | 454 | 455 | 456 | 457 | 458 | 459 | 460 | 461 | 462 | 463 | 464 | 465 | 466 | 467 | 468 | 469 | 470 | 471 | 472 | 473 | 474 | 475 | 476 | 477 | 478 | 479 | 480 | 481 | 482 | 483 | 484 | 485 | 486 | 487 | 488 | 489 | 490 | 491 | 492 | 493 | 494 | 495 | 496 | 497 | 498 | 499 | 500 | 501 | 502 | 503 | 504 | 505 | 506 | 507 | 508 | 509 | 510 | 511 | 512 | 513 | 514 | 515 | 516 | 517 | 518 | 519 | 520 | 521 | 522 | 523 | 524 | 525 | 526 | 527 | 528 | 529 | 530 | 531 | 532 | 533 | 534 | 535 | 536 | 537 | 538 | 539 | 540 | 541 | 542 | 543 | 544 | 545 | 546 | 547 | 548 | 549 | 550 | 551 | 552 | 553 | 554 | 555 | 556 | 557 | 558 | 559 | 560 | 561 | 562 | 563 | 564 | 565 | 566 | 567 | 568 | 569 | 570 | 571 | 572 | 573 | 574 | 575 | 576 | 577 | 578 | 579 | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | nan |
| 3030.93 | 2564 | 2187.73 | 1411.13 | 1.3602 | 100 | 97.6133 | 0.1242 | 1.5005 | 0.0162 | -0.0034 | 0.9455 | 202.44 | 0 | 7.9558 | 414.871 | 10.0433 | 0.968 | 192.396 | 12.519 | 1.4026 | -5419 | 2916.5 | -4043.75 | 751 | 0.8955 | 1.773 | 3.049 | 64.2333 | 2.0222 | 0.1632 | 3.5191 | 83.3971 | 9.5126 | 50.617 | 64.2588 | 49.383 | 66.3141 | 86.9555 | 117.513 | 61.29 | 4.515 | 70 | 352.717 | 10.1841 | 130.369 | 723.309 | 1.3072 | 141.228 | 1 | 624.314 | 218.317 | 0 | 4.592 | 4.841 | 2834 | 0.9317 | 0.9484 | 4.7057 | -1.7264 | 350.926 | 10.6231 | 108.643 | 16.1445 | 21.7264 | 29.5367 | 693.772 | 0.9226 | 148.601 | 1 | 608.17 | 84.0793 | 0 | 0 | 0 | 0.0126 | -0.0206 | 0.0141 | -0.0307 | -0.0083 | -0.0026 | -0.0567 | -0.0044 | 7.2163 | 0.132 | 0 | 2.3895 | 0.969 | 1747.6 | 0.1841 | 8671.93 | -0.3274 | -0.0055 | -0.0001 | 0.0001 | 0.0003 | -0.2786 | 0 | 0.3974 | -0.0251 | 0.0002 | 0.0002 | 0.135 | -0.0042 | 0.0003 | 0.0056 | 0 | -0.2468 | 0.3196 | 0 | 0 | 0 | 0 | 0.946 | 0 | 748.611 | 0.9908 | 58.4306 | 0.6002 | 0.9804 | 6.3788 | 15.88 | 2.639 | 15.94 | 15.93 | 0.8656 | 3.353 | 0.4098 | 3.188 | -0.0473 | 0.7243 | 0.996 | 2.2967 | 1000.73 | 39.2373 | 123 | 111.3 | 75.2 | 46.2 | 350.671 | 0.3948 | 0 | 6.78 | 0.0034 | 0.0898 | 0.085 | 0.0358 | 0.0328 | 12.2566 | 0 | 4.271 | 10.284 | 0.4734 | 0.0167 | 11.8901 | 0.41 | 0.0506 | 0 | 0 | 1017 | 967 | 1066 | 368 | 0.09 | 0.048 | 0.095 | 2 | 0.9 | 0.069 | 0.046 | 0.725 | 0.1139 | 0.3183 | 0.5888 | 0.3184 | 0.9499 | 0.3979 | 0.16 | 0 | 0 | 20.95 | 0.333 | 12.49 | 16.713 | 0.0803 | 5.72 | 0 | 11.19 | 65.363 | 0 | 0 | 0 | 0 | 0 | 0 | 0.292 | 5.38 | 20.1 | 0.296 | 10.62 | 10.3 | 5.38 | 4.04 | 16.23 | 0.2951 | 8.64 | 0 | 10.3 | 97.314 | 0 | 0.0772 | 0.0599 | 0.07 | 0.0547 | 0.0704 | 0.052 | 0.0301 | 0.1135 | 3.4789 | 0.001 | 0 | 0.0707 | 0.0211 | 175.217 | 0.0315 | 1940.4 | 0 | 0.0744 | 0.0546 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0027 | 0.004 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0188 | 0 | 219.945 | 0.0011 | 2.8374 | 0.0189 | 0.005 | 0.4269 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0472 | 40.855 | 4.5152 | 30.9815 | 33.9606 | 22.9057 | 15.9525 | 110.214 | 0.131 | 0 | 2.5883 | 0.001 | 0.0319 | 0.0197 | 0.012 | 0.0109 | 3.9321 | 0 | 1.5123 | 3.5811 | 0.1337 | 0.0055 | 3.8447 | 0.1077 | 0.0167 | 0 | 0 | 418.136 | 398.318 | 496.158 | 158.333 | 0.0373 | 0.0202 | 0.0462 | 0.6083 | 0.3032 | 0.02 | 0.0174 | 0.2827 | 0.0434 | 0.1342 | 0.2419 | 0.1343 | 0.367 | 0.1431 | 0.061 | 0 | 0 | 0 | 6.2698 | 0.1181 | 3.8208 | 5.3737 | 0.0254 | 1.6252 | 0 | 3.2461 | 18.0118 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0752 | 1.5989 | 6.5893 | 0.0913 | 3.0911 | 8.4654 | 1.5989 | 1.2293 | 5.3406 | 0.0867 | 2.8551 | 0 | 2.9971 | 31.8843 | 0 | 0 | 0 | 0.0215 | 0.0274 | 0.0315 | 0.0238 | 0.0206 | 0.0238 | 0.0144 | 0.0491 | 1.2708 | 0.0004 | 0 | 0.0229 | 0.0065 | 55.2039 | 0.0105 | 560.266 | 0 | 0.017 | 0.0148 | 0.0124 | 0.0114 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.001 | 0.0013 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0055 | 0 | 61.5932 | 0.0003 | 0.9967 | 0.0082 | 0.0017 | 0.1437 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0151 | 14.2396 | 1.4392 | 5.6188 | 3.6721 | 2.9329 | 2.1118 | 24.8504 | 29.0271 | 0 | 6.9458 | 2.738 | 5.9846 | 525.096 | 0 | 3.4641 | 6.0544 | 0 | 53.684 | 2.4788 | 4.7141 | 1.7275 | 6.18 | 3.275 | 3.6084 | 18.7673 | 33.1562 | 26.3617 | 49.0013 | 10.0503 | 2.7073 | 3.1158 | 3.1136 | 44.5055 | 42.2737 | 1.3071 | 0.8693 | 1.1975 | 0.6288 | 0.9163 | 0.6448 | 1.4324 | 0.4576 | 0.1362 | 0 | 0 | 0 | 5.9396 | 3.2698 | 9.5805 | 2.3106 | 6.1463 | 4.0502 | 0 | 1.7924 | 29.9394 | 0 | 0 | 0 | 0 | 0 | 0 | 6.2052 | 311.638 | 5.7277 | 2.7864 | 9.7752 | 63.7987 | 24.7625 | 13.6778 | 2.3394 | 31.9893 | 5.8142 | 0 | 1.6936 | 115.741 | 0 | 613.307 | 291.484 | 494.7 | 178.176 | 843.114 | 0 | 53.1098 | 0 | 48.2091 | 0.7578 | 0 | 2.957 | 2.1739 | 10.0261 | 17.1202 | 22.3756 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 64.6707 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.9864 | 0 | 29.3804 | 0.1094 | 4.856 | 3.1406 | 0.5064 | 6.6926 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.057 | 4.0825 | 11.5074 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 1.0616 | 395.57 | 75.752 | 0.4234 | 12.93 | 0.78 | 0.1827 | 5.7349 | 0.3363 | 39.8842 | 3.2687 | 1.0297 | 1.0344 | 0.4385 | 0.1039 | 42.3877 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 533.85 | 2.1113 | 8.95 | 0.3157 | 3.0624 | 0.1026 | 1.6765 | 14.9509 | 0 | 0 | 0 | 0 | 0.5005 | 0.0118 | 0.0035 | 2.363 | 0 | 0 | 0 | 0 | -1 |
| 3095.78 | 2465.14 | 2230.42 | 1463.66 | 0.8294 | 100 | 102.343 | 0.1247 | 1.4966 | -0.0005 | -0.0148 | 0.9627 | 200.547 | 0 | 10.1548 | 414.735 | 9.2599 | 0.9701 | 191.287 | 12.4608 | 1.3825 | -5441.5 | 2604.25 | -3498.75 | -1640.25 | 1.2973 | 2.0143 | 7.39 | 68.4222 | 2.2667 | 0.2102 | 3.4171 | 84.9052 | 9.7997 | 50.6596 | 64.2828 | 49.3404 | 64.9193 | 87.5241 | 118.119 | 78.25 | 2.773 | 70 | 352.245 | 10.0373 | 133.173 | 724.826 | 1.2887 | 145.845 | 1 | 631.262 | 205.169 | 0 | 4.59 | 4.842 | 2853 | 0.9324 | 0.9479 | 4.682 | 0.8073 | 352.007 | 10.3092 | 113.98 | 10.9036 | 19.1927 | 27.6301 | 697.196 | 1.1598 | 154.371 | 1 | 620.358 | 82.3494 | 0 | 0 | 0 | -0.0039 | -0.0198 | 0.0004 | -0.044 | -0.0358 | -0.012 | -0.0377 | 0.0017 | 6.8043 | 0.1358 | 0 | 2.3754 | 0.9894 | 1931.65 | 0.1874 | 8407.03 | 0.1455 | -0.0015 | 0 | -0.0005 | 0.0001 | 0.5854 | 0 | -0.9353 | -0.0158 | -0.0004 | -0.0004 | -0.0752 | -0.0045 | 0.0002 | 0.0015 | 0 | 0.0772 | -0.0903 | 0 | 0 | 0 | 0 | 0.9425 | 0 | 731.252 | 0.9902 | 58.668 | 0.5958 | 0.9731 | 6.5061 | 15.88 | 2.541 | 15.91 | 15.88 | 0.8703 | 2.771 | 0.4138 | 3.272 | -0.0946 | 0.8122 | 0.9985 | 2.2932 | 998.108 | 37.9213 | 98 | 80.3 | 81 | 56.2 | 219.768 | 0.2301 | 0 | 5.7 | 0.0049 | 0.1356 | 0.06 | 0.0547 | 0.0204 | 12.3319 | 0 | 6.285 | 13.077 | 0.5666 | 0.0144 | 11.8428 | 0.35 | 0.0437 | 0 | 0 | 568 | 59 | 297 | 3277 | 0.112 | 0.115 | 0.124 | 2.2 | 1.1 | 0.079 | 0.561 | 1.0498 | 0.1917 | 0.4115 | 0.6582 | 0.4115 | 1.0181 | 0.2315 | 0.325 | 0 | 0 | 17.99 | 0.439 | 10.14 | 16.358 | 0.0892 | 6.92 | 0 | 9.05 | 82.986 | 0 | 0 | 0 | 0 | 0 | 0 | 0.222 | 3.74 | 19.59 | 0.316 | 11.65 | 8.02 | 3.74 | 3.659 | 15.078 | 0.358 | 8.96 | 0 | 8.02 | 134.25 | 0 | 0.0566 | 0.0488 | 0.1651 | 0.1578 | 0.0468 | 0.0987 | 0.0734 | 0.0747 | 3.9578 | 0.005 | 0 | 0.0761 | 0.0014 | 128.429 | 0.0238 | 1988 | 0 | 0.0203 | 0.0236 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0064 | 0.0036 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0154 | 0 | 193.029 | 0.0007 | 3.8999 | 0.0187 | 0.0086 | 0.5749 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0411 | 29.743 | 3.6327 | 29.0598 | 28.9862 | 22.3163 | 17.4008 | 83.5542 | 0.0767 | 0 | 1.8459 | 0.0012 | 0.044 | 0.0171 | 0.0154 | 0.0069 | 3.9011 | 0 | 2.1016 | 3.9483 | 0.1662 | 0.0049 | 3.7836 | 0.1 | 0.0139 | 0 | 0 | 233.987 | 26.5879 | 139.208 | 1529.76 | 0.0502 | 0.0561 | 0.0591 | 0.8151 | 0.3464 | 0.0291 | 0.1822 | 0.3814 | 0.0715 | 0.1667 | 0.263 | 0.1667 | 0.3752 | 0.0856 | 0.1214 | 0 | 0 | 0 | 5.6522 | 0.1417 | 2.9939 | 5.2445 | 0.0264 | 1.8045 | 0 | 2.7661 | 23.623 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0778 | 1.1506 | 5.9247 | 0.0878 | 3.3604 | 7.7421 | 1.1506 | 1.1265 | 5.0108 | 0.1013 | 2.4278 | 0 | 2.489 | 41.708 | 0 | 0 | 0 | 0.0142 | 0.023 | 0.0768 | 0.0729 | 0.0143 | 0.0513 | 0.0399 | 0.0365 | 1.2474 | 0.0017 | 0 | 0.0248 | 0.0005 | 46.3453 | 0.0069 | 677.187 | 0 | 0.0053 | 0.0059 | 0.0081 | 0.0033 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0022 | 0.0013 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0049 | 0 | 65.0999 | 0.0002 | 1.1655 | 0.0068 | 0.0027 | 0.1921 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012 | 10.5837 | 1.0323 | 4.3465 | 2.5939 | 3.2858 | 2.5197 | 15.015 | 27.7464 | 0 | 5.5695 | 3.93 | 9.0604 | 0 | 368.971 | 2.1196 | 6.1491 | 0 | 61.8918 | 3.1531 | 6.1188 | 1.4857 | 6.1911 | 2.8088 | 3.1595 | 10.4383 | 2.2655 | 8.4887 | 199.787 | 8.6336 | 5.7093 | 1.6779 | 3.2153 | 48.5294 | 37.5793 | 16.4174 | 1.2364 | 1.9562 | 0.8123 | 1.0239 | 0.834 | 1.5683 | 0.2645 | 0.2751 | 0 | 0 | 0 | 5.1072 | 4.3737 | 7.6142 | 2.2568 | 6.9233 | 4.7448 | 0 | 1.4336 | 40.4475 | 0 | 0 | 0 | 0 | 0 | 0 | 4.7415 | 463.288 | 5.5652 | 3.0652 | 10.2211 | 73.5536 | 19.4865 | 13.243 | 2.1627 | 30.8643 | 5.8042 | 0 | 1.2928 | 163.025 | 0 | 0 | 246.776 | 0 | 359.044 | 130.635 | 820.79 | 194.437 | 0 | 58.1666 | 3.6822 | 0 | 3.2029 | 0.1441 | 6.6487 | 12.6788 | 23.6469 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 141.436 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.6292 | 0 | 26.397 | 0.0673 | 6.6475 | 3.131 | 0.8832 | 8.837 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.791 | 2.9799 | 9.5796 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 1.3526 | 408.798 | 74.64 | 0.7193 | 16 | 1.33 | 0.2829 | 7.1196 | 0.4989 | 53.1836 | 3.9139 | 1.7819 | 0.9634 | 0.1745 | 0.0375 | 18.1087 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 535.016 | 2.4335 | 5.92 | 0.2653 | 2.0111 | 0.0772 | 1.1065 | 10.9003 | 0.0096 | 0.0201 | 0.006 | 208.204 | 0.5019 | 0.0223 | 0.0055 | 4.4447 | 0.0096 | 0.0201 | 0.006 | 208.204 | -1 |
| 2932.61 | 2559.94 | 2186.41 | 1698.02 | 1.5102 | 100 | 95.4878 | 0.1241 | 1.4436 | 0.0041 | 0.0013 | 0.9615 | 202.018 | 0 | 9.5157 | 416.707 | 9.3144 | 0.9674 | 192.703 | 12.5404 | 1.4123 | -5447.75 | 2701.75 | -4047 | -1916.5 | 1.3122 | 2.0295 | 7.5788 | 67.1333 | 2.3333 | 0.1734 | 3.5986 | 84.7569 | 8.659 | 50.153 | 64.1114 | 49.847 | 65.8389 | 84.7327 | 118.613 | 14.37 | 5.434 | 70 | 364.378 | 9.8783 | 131.803 | 734.792 | 1.2992 | 141.084 | 1 | 637.265 | 185.757 | 0 | 4.486 | 4.748 | 2936 | 0.9139 | 0.9447 | 4.5873 | 23.8245 | 364.536 | 10.1685 | 115.627 | 11.3019 | 16.1755 | 24.2829 | 710.51 | 0.8694 | 145.8 | 1 | 625.964 | 84.7681 | 140.697 | 485.267 | 0 | -0.0078 | -0.0326 | -0.0052 | 0.0213 | -0.0054 | -0.1134 | -0.0182 | 0.0287 | 7.1041 | 0.1362 | 0 | 2.4532 | 0.988 | 1685.85 | 0.1497 | 9317.17 | 0.0553 | 0.0006 | -0.0013 | 0 | 0.0002 | -0.1343 | 0 | -0.1427 | 0.1218 | 0.0006 | -0.0001 | 0.0134 | -0.0026 | -0.0016 | -0.0006 | 0.0013 | -0.0301 | -0.0728 | 0 | 0 | 0 | 0.4684 | 0.9231 | 0 | 718.578 | 0.9899 | 58.4808 | 0.6015 | 0.9772 | 6.4527 | 15.9 | 2.882 | 15.94 | 15.95 | 0.8798 | 3.094 | 0.4777 | 3.272 | -0.1892 | 0.8194 | 0.9978 | 2.2592 | 998.444 | 42.0579 | 89 | 126.4 | 96.5 | 45.1001 | 306.038 | 0.3263 | 0 | 8.33 | 0.0038 | 0.0754 | 0.0483 | 0.0619 | 0.0221 | 8.266 | 0 | 4.819 | 8.443 | 0.4909 | 0.0177 | 8.2054 | 0.47 | 0.0497 | 0 | 0 | 562 | 788 | 759 | 2100 | 0.187 | 0.117 | 0.068 | 2.1 | 1.4 | 0.123 | 0.319 | 1.0824 | 0.0369 | 0.3141 | 0.5753 | 0.3141 | 0.9677 | 0.2706 | 0.326 | 0 | 0 | 17.78 | 0.745 | 13.31 | 22.912 | 0.1959 | 9.21 | 0 | 17.87 | 60.11 | 0 | 0 | 0 | 0 | 0 | 0 | 0.139 | 5.09 | 19.75 | 0.949 | 9.71 | 16.73 | 5.09 | 11.059 | 22.624 | 0.1164 | 13.3 | 0 | 16.73 | 79.618 | 0 | 0.0339 | 0.0494 | 0.0696 | 0.0406 | 0.0401 | 0.084 | 0.0349 | 0.0718 | 2.4266 | 0.0014 | 0 | 0.0963 | 0.0152 | 182.496 | 0.0284 | 839.601 | 0 | 0.0192 | 0.017 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0062 | 0.004 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1729 | 0.0273 | 0 | 104.404 | 0.0007 | 4.1446 | 0.0733 | 0.0063 | 0.4166 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0487 | 29.621 | 3.9133 | 23.551 | 41.3837 | 32.6256 | 15.7716 | 97.3868 | 0.1117 | 0 | 2.5274 | 0.0012 | 0.0249 | 0.0152 | 0.0157 | 0.0075 | 2.8705 | 0 | 1.5306 | 2.5493 | 0.1479 | 0.0059 | 2.8046 | 0.1185 | 0.0167 | 0 | 0 | 251.454 | 329.641 | 325.067 | 902.458 | 0.08 | 0.0583 | 0.0326 | 0.6964 | 0.4031 | 0.0416 | 0.1041 | 0.3846 | 0.0151 | 0.1288 | 0.2268 | 0.1288 | 0.3677 | 0.1175 | 0.1261 | 0 | 0 | 0 | 5.7247 | 0.2682 | 3.8541 | 6.1797 | 0.0546 | 2.568 | 0 | 4.6067 | 16.0104 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0243 | 1.5481 | 5.9453 | 0.2777 | 3.16 | 8.9855 | 1.5481 | 2.9844 | 6.2277 | 0.0353 | 3.7663 | 0 | 5.6983 | 24.7959 | 13.5664 | 15.4488 | 0 | 0.0105 | 0.0208 | 0.0327 | 0.0171 | 0.0116 | 0.0428 | 0.0154 | 0.0383 | 0.7786 | 0.0005 | 0 | 0.0302 | 0.0046 | 58.0575 | 0.0092 | 283.662 | 0 | 0.0054 | 0.0043 | 0.003 | 0.0037 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0021 | 0.0015 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0221 | 0.01 | 0 | 28.7334 | 0.0003 | 1.2356 | 0.019 | 0.002 | 0.1375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019 | 11.4871 | 1.1798 | 4.0782 | 4.3102 | 3.7696 | 2.0627 | 18.0233 | 21.6062 | 0 | 8.7236 | 3.0609 | 5.2231 | 0 | 0 | 2.2943 | 4.0917 | 0 | 50.6425 | 2.0261 | 5.2707 | 1.8268 | 4.2581 | 3.7479 | 3.522 | 10.3162 | 29.1663 | 18.7546 | 109.575 | 14.2503 | 5.765 | 0.8972 | 3.1281 | 60 | 70.9161 | 8.8647 | 1.2771 | 0.4264 | 0.6263 | 0.8973 | 0.6301 | 1.4698 | 0.3194 | 0.2748 | 0 | 0 | 0 | 4.8795 | 7.5418 | 10.0984 | 3.1182 | 15.079 | 6.528 | 0 | 2.8042 | 32.3594 | 0 | 0 | 0 | 0 | 0 | 0 | 3.0301 | 21.3645 | 5.4178 | 9.3327 | 8.3977 | 148.029 | 31.4674 | 45.5423 | 3.1842 | 13.3923 | 9.1221 | 0 | 2.6727 | 93.9245 | 0 | 434.267 | 151.767 | 0 | 190.387 | 746.915 | 74.0741 | 191.758 | 250.174 | 34.1573 | 1.0281 | 0 | 3.9238 | 1.5357 | 10.8251 | 18.9849 | 9.0113 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 240.777 | 244.275 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 36.9067 | 2.9626 | 0 | 14.5293 | 0.0751 | 7.087 | 12.1831 | 0.6451 | 6.4568 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.1538 | 2.9667 | 9.3046 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 0.7942 | 411.136 | 74.654 | 0.1832 | 16.16 | 0.85 | 0.0857 | 7.1619 | 0.3752 | 23.0713 | 3.9306 | 1.1386 | 1.5021 | 0.3718 | 0.1233 | 24.7524 | 267.064 | 0.9032 | 1.1 | 0.6219 | 0.4122 | 0.2562 | 0.4119 | 68.8489 | 535.024 | 2.0293 | 11.21 | 0.1882 | 4.0923 | 0.064 | 2.0952 | 9.2721 | 0.0584 | 0.0484 | 0.0148 | 82.8602 | 0.4958 | 0.0157 | 0.0039 | 3.1745 | 0.0584 | 0.0484 | 0.0148 | 82.8602 | 1 |
| 2988.72 | 2479.9 | 2199.03 | 909.793 | 1.3204 | 100 | 104.237 | 0.1217 | 1.4882 | -0.0124 | -0.0033 | 0.9629 | 201.848 | 0 | 9.6052 | 422.289 | 9.6924 | 0.9687 | 192.156 | 12.4782 | 1.4011 | -5468.25 | 2648.25 | -4515 | -1657.25 | 1.3137 | 2.0038 | 7.3145 | 62.9333 | 2.6444 | 0.2071 | 3.3813 | 84.9105 | 8.6789 | 50.51 | 64.1125 | 49.49 | 65.1951 | 86.6867 | 117.044 | 76.9 | 1.279 | 70 | 363.027 | 9.9305 | 131.803 | 733.878 | 1.3027 | 142.543 | 1 | 637.373 | 189.908 | 0 | 4.486 | 4.748 | 2936 | 0.9139 | 0.9447 | 4.5873 | 24.3791 | 361.458 | 10.2112 | 116.182 | 13.5597 | 15.6209 | 23.4736 | 710.404 | 0.9761 | 147.655 | 1 | 625.294 | 70.2289 | 160.321 | 464.974 | 0 | -0.0555 | -0.0461 | -0.04 | 0.04 | 0.0676 | -0.1051 | 0.0028 | 0.0277 | 7.5925 | 0.1302 | 0 | 2.4004 | 0.9904 | 1752.1 | 0.1958 | 8205.7 | 0.0697 | -0.0003 | -0.0021 | -0.0001 | 0.0002 | 0.0411 | 0 | 0.0177 | -0.0195 | -0.0002 | 0 | -0.0699 | -0.0059 | 0.0003 | 0.0003 | 0.0021 | -0.0483 | -0.118 | 0 | 0 | 0 | 0.4647 | 0.9564 | 0 | 709.087 | 0.9906 | 58.6635 | 0.6016 | 0.9761 | 6.4935 | 15.55 | 3.132 | 15.61 | 15.59 | 1.366 | 2.48 | 0.5176 | 3.119 | 0.2838 | 0.7244 | 0.9961 | 2.3802 | 980.451 | 41.1025 | 127 | 118 | 123.7 | 47.8 | 162.432 | 0.1915 | 0 | 5.51 | 0.003 | 0.114 | 0.0393 | 0.0613 | 0.019 | 13.2651 | 0 | 9.073 | 15.241 | 1.3029 | 0.015 | 11.9738 | 0.35 | 0.0699 | 0 | 0 | 859 | 355 | 3433 | 3004 | 0.068 | 0.108 | 0.1 | 1.7 | 0.9 | 0.086 | 0.241 | 0.9386 | 0.0356 | 0.2618 | 0.4391 | 0.2618 | 0.8567 | 0.2452 | 0.39 | 0 | 0 | 16.22 | 0.693 | 14.67 | 22.562 | 0.1786 | 5.69 | 0 | 18.2 | 52.571 | 0 | 0 | 0 | 0 | 0 | 0 | 0.139 | 5.92 | 23.6 | 1.264 | 10.63 | 13.56 | 5.92 | 11.382 | 24.32 | 0.3458 | 9.56 | 0 | 21.97 | 104.95 | 0 | 0.1248 | 0.0463 | 0.1223 | 0.0354 | 0.0708 | 0.0754 | 0.0643 | 0.0932 | 5.5398 | 0.0023 | 0 | 0.0764 | 0.0015 | 152.089 | 0.0573 | 820.4 | 0 | 0.0152 | 0.0149 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0067 | 0.004 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0191 | 0.0234 | 0 | 94.0954 | 0.001 | 3.2119 | 0.0406 | 0.0072 | 0.4212 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0513 | 31.83 | 3.1959 | 33.896 | 37.8477 | 44.3906 | 16.9347 | 50.3631 | 0.0581 | 0 | 2.1775 | 0.0007 | 0.0417 | 0.0115 | 0.0172 | 0.0063 | 4.2154 | 0 | 2.896 | 4.0526 | 0.3882 | 0.0049 | 3.9403 | 0.0916 | 0.0245 | 0 | 0 | 415.505 | 157.089 | 1572.69 | 1377.43 | 0.0285 | 0.0445 | 0.0465 | 0.6305 | 0.3046 | 0.0286 | 0.0824 | 0.3483 | 0.0128 | 0.1004 | 0.1701 | 0.1004 | 0.3465 | 0.0973 | 0.1675 | 0 | 0 | 0 | 5.444 | 0.2004 | 4.19 | 6.3329 | 0.0479 | 1.7339 | 0 | 4.966 | 15.7375 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0243 | 1.7317 | 6.6262 | 0.3512 | 3.2699 | 9.402 | 1.7317 | 3.0672 | 6.6839 | 0.0928 | 3.0229 | 0 | 6.3292 | 29.0339 | 8.4026 | 4.8851 | 0 | 0.0407 | 0.0198 | 0.0531 | 0.0167 | 0.0224 | 0.0422 | 0.0273 | 0.0484 | 1.8222 | 0.0006 | 0 | 0.0252 | 0.0004 | 45.7058 | 0.0188 | 309.849 | 0 | 0.0046 | 0.0049 | 0.0028 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0024 | 0.0014 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0038 | 0.0068 | 0 | 32.4228 | 0.0003 | 1.1135 | 0.0132 | 0.0023 | 0.1348 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0155 | 13.3972 | 1.1907 | 5.6363 | 3.9482 | 4.9881 | 2.1737 | 17.8537 | 14.5054 | 0 | 5.286 | 2.4643 | 7.6602 | 317.736 | 0 | 1.9689 | 6.5718 | 0 | 94.4594 | 3.6091 | 13.442 | 1.5441 | 6.2313 | 2.8049 | 4.9898 | 15.7089 | 13.4051 | 76.0354 | 181.264 | 5.176 | 5.3899 | 1.3671 | 2.7013 | 34.0336 | 41.5236 | 7.1274 | 1.1054 | 0.4097 | 0.5183 | 0.6849 | 0.529 | 1.3141 | 0.2829 | 0.3332 | 0 | 0 | 0 | 4.468 | 6.9785 | 11.1303 | 3.0744 | 13.7105 | 3.9918 | 0 | 2.8555 | 27.6824 | 0 | 0 | 0 | 0 | 0 | 0 | 3.0301 | 24.2831 | 6.5291 | 12.3786 | 9.1494 | 100.002 | 37.8979 | 48.4887 | 3.4234 | 35.4323 | 6.4746 | 0 | 3.5135 | 149.44 | 0 | 225.017 | 100.488 | 305.75 | 88.5553 | 104.666 | 71.7583 | 0 | 336.766 | 72.9635 | 1.767 | 0 | 3.1817 | 0.1488 | 8.6804 | 29.2542 | 9.9979 | 0 | 0 | 711.642 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 113.559 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4.12 | 2.4416 | 0 | 13.2699 | 0.0977 | 5.4751 | 6.7553 | 0.7404 | 6.4865 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.1565 | 3.2465 | 7.7754 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 1.165 | 372.822 | 72.442 | 1.8804 | 131.68 | 39.33 | 0.6812 | 56.9303 | 17.4781 | 161.408 | 35.3198 | 54.2917 | 1.1613 | 0.7288 | 0.271 | 62.7572 | 268.228 | 0.6511 | 7.32 | 0.163 | 3.5611 | 0.067 | 2.729 | 25.0363 | 530.568 | 2.0253 | 9.33 | 0.1738 | 2.8971 | 0.0525 | 1.7585 | 8.5831 | 0.0202 | 0.0149 | 0.0044 | 73.8432 | 0.499 | 0.0103 | 0.0025 | 2.0544 | 0.0202 | 0.0149 | 0.0044 | 73.8432 | -1 |
| 3032.24 | 2502.87 | 2233.37 | 1326.52 | 1.5334 | 100 | 100.397 | 0.1235 | 1.5031 | -0.0031 | -0.0072 | 0.9569 | 201.942 | 0 | 10.5661 | 420.592 | 10.3387 | 0.9735 | 191.604 | 12.4735 | 1.3888 | -5476.25 | 2635.25 | -3987.5 | 117 | 1.2887 | 1.9912 | 7.2748 | 62.8333 | 3.1556 | 0.2696 | 3.2728 | 86.3269 | 8.7677 | 50.248 | 64.1511 | 49.752 | 66.1542 | 86.1468 | 121.436 | 76.39 | 2.209 | 70 | 353.34 | 10.4091 | 176.314 | 789.752 | 1.0341 | 138.088 | 1 | 667.742 | 233.549 | 0 | 4.624 | 4.894 | 2865 | 0.9298 | 0.9449 | 4.6414 | -12.2945 | 355.081 | 9.7948 | 144.019 | 21.9782 | 32.2945 | 44.1498 | 745.602 | 0.9256 | 146.664 | 1 | 645.764 | 65.8417 | 0 | 0 | 0 | -0.0534 | 0.0183 | -0.0167 | -0.0449 | 0.0034 | -0.0178 | -0.0123 | -0.0048 | 7.5017 | 0.1342 | 0 | 2.453 | 0.9902 | 1828.38 | 0.1829 | 9014.46 | 0.0448 | -0.0077 | -0.0001 | -0.0001 | -0.0001 | 0.2189 | 0 | -0.6704 | -0.0167 | 0.0004 | -0.0003 | 0.0696 | -0.0045 | 0.0002 | 0.0078 | 0 | -0.0799 | -0.2038 | 0 | 0 | 0 | 0 | 0.9424 | 0 | 796.595 | 0.9908 | 58.3858 | 0.5913 | 0.9628 | 6.3551 | 15.75 | 3.148 | 15.73 | 15.71 | 0.946 | 3.027 | 0.5328 | 3.299 | -0.5677 | 0.778 | 1.001 | 2.3715 | 993.127 | 38.1448 | 119 | 143.2 | 123.1 | 48.8 | 296.303 | 0.3744 | 0 | 3.64 | 0.0041 | 0.0634 | 0.0451 | 0.0623 | 0.024 | 14.2354 | 0 | 9.005 | 12.506 | 0.4434 | 0.0126 | 13.9047 | 0.43 | 0.0538 | 0 | 0 | 699 | 283 | 1747 | 1443 | 0.147 | 0.04 | 0.113 | 3.9 | 0.8 | 0.101 | 0.499 | 0.576 | 0.0631 | 0.3053 | 0.583 | 0.3053 | 0.8285 | 0.1308 | 0.922 | 0 | 0 | 15.24 | 0.282 | 10.85 | 37.715 | 0.1189 | 3.98 | 0 | 25.54 | 72.149 | 0 | 0 | 0 | 0 | 0 | 0 | 0.25 | 5.52 | 15.76 | 0.519 | 10.71 | 19.77 | 5.52 | 8.446 | 33.832 | 0.3951 | 9.09 | 0 | 19.77 | 92.307 | 0 | 0.0915 | 0.0506 | 0.0769 | 0.1079 | 0.0797 | 0.1047 | 0.0924 | 0.1015 | 4.1338 | 0.003 | 0 | 0.0802 | 0.0004 | 69.151 | 0.197 | 1406.4 | 0 | 0.0227 | 0.0272 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0067 | 0.0031 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.024 | 0 | 149.217 | 0.0006 | 2.5775 | 0.0177 | 0.0214 | 0.4051 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0488 | 19.862 | 3.6163 | 34.125 | 55.9626 | 53.0876 | 17.4864 | 88.7672 | 0.1092 | 0 | 1.0929 | 0.0013 | 0.0257 | 0.0116 | 0.0163 | 0.008 | 4.4239 | 0 | 3.2376 | 3.6536 | 0.1293 | 0.004 | 4.3474 | 0.1275 | 0.0181 | 0 | 0 | 319.125 | 128.03 | 799.588 | 628.308 | 0.0755 | 0.0181 | 0.0476 | 1.35 | 0.2698 | 0.032 | 0.1541 | 0.2155 | 0.031 | 0.1354 | 0.2194 | 0.1354 | 0.3072 | 0.0582 | 0.3574 | 0 | 0 | 0 | 4.8956 | 0.0766 | 2.913 | 11.0583 | 0.0327 | 1.1229 | 0 | 7.3296 | 23.116 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0822 | 1.6216 | 4.7279 | 0.1773 | 3.155 | 9.7777 | 1.6216 | 2.5923 | 10.5352 | 0.1301 | 3.0939 | 0 | 6.3767 | 32.0537 | 0 | 0 | 0 | 0.0246 | 0.0221 | 0.0329 | 0.0522 | 0.0256 | 0.0545 | 0.0476 | 0.0463 | 1.553 | 0.001 | 0 | 0.0286 | 0.0001 | 21.0312 | 0.0573 | 494.737 | 0 | 0.0063 | 0.0077 | 0.0052 | 0.0027 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0025 | 0.0012 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0089 | 0 | 57.2692 | 0.0002 | 0.8495 | 0.0065 | 0.0077 | 0.1356 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0165 | 7.1493 | 1.1704 | 5.3823 | 4.7226 | 4.9184 | 2.185 | 22.3369 | 24.4142 | 0 | 3.6256 | 3.3208 | 4.2178 | 0 | 866.029 | 2.5046 | 7.0492 | 0 | 85.2255 | 2.9734 | 4.2892 | 1.2943 | 7.257 | 3.4473 | 3.8754 | 12.7642 | 10.739 | 43.8119 | 0 | 11.4064 | 2.0088 | 1.5533 | 6.2069 | 25.3521 | 37.4691 | 15.247 | 0.6672 | 0.7198 | 0.6076 | 0.9088 | 0.6136 | 1.2524 | 0.1518 | 0.7592 | 0 | 0 | 0 | 4.3131 | 2.7092 | 6.1538 | 4.7756 | 11.4945 | 2.8822 | 0 | 3.8248 | 30.8924 | 0 | 0 | 0 | 0 | 0 | 0 | 5.3863 | 44.898 | 4.4384 | 5.2987 | 7.4365 | 89.9529 | 17.0927 | 19.1303 | 4.5375 | 42.6838 | 6.1979 | 0 | 3.0615 | 140.195 | 0 | 171.449 | 276.881 | 461.862 | 240.178 | 0 | 587.377 | 748.178 | 0 | 55.1057 | 2.2358 | 0 | 3.2712 | 0.0372 | 3.7821 | 107.691 | 15.6016 | 0 | 293.14 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 148.066 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.5512 | 0 | 18.7319 | 0.0616 | 4.4146 | 2.9954 | 2.2181 | 6.3745 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.0579 | 1.9999 | 9.4805 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 1.4636 | 399.914 | 79.156 | 1.0388 | 19.63 | 1.98 | 0.4287 | 9.7608 | 0.8311 | 70.9706 | 4.9086 | 2.5014 | 0.9778 | 0.2156 | 0.0461 | 22.05 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 532.015 | 2.0275 | 8.83 | 0.2224 | 3.1776 | 0.0706 | 1.6597 | 10.9698 | 0 | 0 | 0 | 0 | 0.48 | 0.4766 | 0.1045 | 99.3032 | 0.0202 | 0.0149 | 0.0044 | 73.8432 | -1 |
| 2946.25 | 2432.84 | 2233.37 | 1326.52 | 1.5334 | 100 | 100.397 | 0.1235 | 1.5287 | 0.0167 | 0.0055 | 0.9699 | 200.472 | 0 | 8.6617 | 414.243 | 9.2441 | 0.9747 | 191.228 | 12.4935 | 1.3836 | -6058 | 2953.75 | -3906.5 | 193.75 | 0.893 | 1.7775 | 3.0505 | 62.3778 | 1.6333 | 0.1394 | 3.52 | 85.4233 | 9.6484 | 50.5795 | 64.072 | 49.4205 | 66.2949 | 87.0273 | 117.493 | 59.94 | 3.024 | 70 | 360.287 | 9.7804 | 142.259 | 746.869 | 1.188 | 137.647 | 1 | 640.194 | 192.77 | 0 | 4.636 | 4.915 | 2865 | 0.9316 | 0.9433 | 4.6275 | 28.2955 | 360.241 | 9.8344 | 130.554 | 7.618 | 11.7045 | 18.3685 | 728.501 | 0.9227 | 144.698 | 1 | 635.494 | 70.3707 | 0 | 0 | 0 | 0.0198 | -0.055 | -0.001 | -0.0074 | -0.0026 | -0.0853 | -0.0111 | 0.021 | 6.7509 | 0.1417 | 0 | 2.3745 | 0.9888 | 1832.63 | 0.2099 | 7869.7 | -0.113 | 0.0009 | -0.0004 | -0.0002 | 0.0001 | 0.1925 | 0 | -0.224 | -0.0419 | -0.0002 | -0.0001 | 0.0265 | -0.0052 | 0.0006 | -0.0008 | 0.0004 | -0.2601 | 0.1324 | 0 | 0 | 0 | 0.4651 | 0.9427 | 0 | 748.089 | 0.9907 | 58.656 | 0.6081 | 0.9632 | 6.3186 | 15.88 | 2.541 | 15.91 | 15.88 | 0.8703 | 2.771 | 0.4138 | 3.272 | -0.0946 | 0.8122 | 0.9985 | 2.2932 | 998.108 | 37.9213 | 123 | 159.8 | 119.3 | 48.8 | 296.303 | 0.3744 | 0 | 3.64 | 0.0041 | 0.0709 | 0.0581 | 0.0478 | 0.0141 | 12.3665 | 0 | 5.369 | 10.42 | 0.5564 | 0.0106 | 11.8948 | 0.45 | 0.0511 | 0 | 0 | 2089 | 910 | 323 | 1157 | 0.065 | 0.036 | 0.045 | 1.7 | 0.9 | 0.106 | 0.123 | 0.6308 | 0.3176 | 0.3824 | 0.5646 | 0.3824 | 0.7408 | 0.2789 | 0.219 | 0 | 0 | 19.7 | 0.482 | 14.38 | 35.535 | 0.1552 | 7.92 | 0 | 21.62 | 82.556 | 0 | 0 | 0 | 0 | 0 | 0 | 0.244 | 6.61 | 24.22 | 1.003 | 11.8 | 21.78 | 6.61 | 9.679 | 34.8069 | 0.5217 | 12.32 | 0 | 34.99 | 111.952 | 0 | 0.0645 | 0.0391 | 0.0849 | 0.0614 | 0.0494 | 0.0668 | 0.0803 | 0.0575 | 2.8799 | 0.0117 | 0 | 0.0662 | 0.0028 | 129.173 | 0.031 | 1132.3 | 0 | 0.0362 | 0.019 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0036 | 0.0035 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0217 | 0.0198 | 0 | 158.273 | 0.0007 | 2.6668 | 0.0268 | 0.028 | 0.4484 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0411 | 29.743 | 3.6327 | 32.0878 | 52.6671 | 36.4696 | 17.4864 | 88.7672 | 0.1092 | 0 | 1.0929 | 0.0013 | 0.0226 | 0.0155 | 0.0155 | 0.0048 | 3.9449 | 0 | 1.4873 | 3.1727 | 0.1614 | 0.0034 | 3.8352 | 0.1275 | 0.0176 | 0 | 0 | 982.823 | 384.61 | 152.435 | 478.15 | 0.0279 | 0.0158 | 0.0203 | 0.632 | 0.3162 | 0.0405 | 0.0439 | 0.2442 | 0.1379 | 0.1515 | 0.2379 | 0.1515 | 0.2839 | 0.101 | 0.0833 | 0 | 0 | 0 | 5.5901 | 0.1505 | 3.8197 | 10.178 | 0.0453 | 2.3901 | 0 | 5.9858 | 25.2892 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0789 | 1.9589 | 6.9023 | 0.3364 | 3.3583 | 10.4221 | 1.9589 | 2.6806 | 9.6731 | 0.1582 | 3.7242 | 0 | 9.5854 | 33.4938 | 0 | 0 | 0 | 0.0166 | 0.0181 | 0.041 | 0.0277 | 0.0148 | 0.0315 | 0.0442 | 0.0259 | 0.969 | 0.0036 | 0 | 0.0227 | 0.0012 | 42.1498 | 0.0092 | 335.598 | 0 | 0.0095 | 0.0048 | 0.0033 | 0.0027 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0013 | 0.0011 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0058 | 0.0078 | 0 | 58.2605 | 0.0003 | 0.923 | 0.0077 | 0.0081 | 0.152 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012 | 10.5837 | 1.0323 | 5.4262 | 5.4238 | 4.9037 | 2.185 | 22.3369 | 24.4142 | 0 | 3.6256 | 3.3208 | 4.638 | 347.774 | 865.158 | 1.4577 | 6.1687 | 0 | 61.9853 | 2.5154 | 6.0186 | 1.0841 | 6.2202 | 3.6019 | 3.6904 | 34.4833 | 30.8083 | 8.2683 | 597.161 | 7.2788 | 2.0253 | 1.4752 | 2.7253 | 55.102 | 76.0159 | 3.4943 | 0.7384 | 3.2918 | 0.756 | 0.8812 | 0.7738 | 1.1174 | 0.3205 | 0.1864 | 0 | 0 | 0 | 5.4679 | 4.9282 | 10.1083 | 4.7579 | 13.0665 | 5.7538 | 0 | 3.3771 | 42.8261 | 0 | 0 | 0 | 0 | 0 | 0 | 5.2729 | 23.3606 | 6.7233 | 10.1989 | 9.0384 | 285.9 | 56.4737 | 52.6935 | 4.7779 | 56.539 | 8.5143 | 0 | 5.506 | 159.089 | 0 | 325.347 | 71.0586 | 0 | 826.936 | 0 | 78.3348 | 723.423 | 273.81 | 42.6594 | 8.2199 | 0 | 2.7883 | 0.2873 | 7.0485 | 14.7656 | 14.3881 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 68.7351 | 622.222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4.6687 | 2.1027 | 0 | 21.157 | 0.0706 | 4.5466 | 4.406 | 2.9077 | 7.097 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.791 | 2.9799 | 9.5796 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 1.2708 | 412.222 | 80.326 | 1.105 | 16.06 | 1.65 | 0.5329 | 7.2448 | 0.6268 | 86.9463 | 3.896 | 2.0541 | 0.9469 | 0.29 | 0.0604 | 30.6277 | 254.006 | 0.8444 | 4.75 | 0.1905 | 1.8784 | 0.0743 | 1.87 | 22.5598 | 534.209 | 2.3236 | 8.91 | 0.3201 | 2.2598 | 0.0899 | 1.6679 | 13.7755 | 0.0342 | 0.0151 | 0.0052 | 44.0077 | 0.4949 | 0.0189 | 0.0044 | 3.8276 | 0.0342 | 0.0151 | 0.0052 | 44.0077 | -1 |
| 3030.27 | 2430.12 | 2230.42 | 1463.66 | 0.8294 | 100 | 102.343 | 0.1247 | 1.5816 | -0.027 | 0.0105 | 0.9591 | 202.09 | 0 | 9.035 | 415.885 | 9.999 | 0.9667 | 192.091 | 12.4608 | 1.4067 | -6154 | 2691.75 | -3914.75 | 580.25 | 0.9063 | 1.7715 | 3.0515 | 60.8 | 2.4889 | 0.2081 | 3.4927 | 87.1543 | 9.1502 | 50.2847 | 64.2476 | 49.7153 | 66.2237 | 86.374 | 121.866 | 74.46 | 3.978 | 70 | 352.184 | 10.062 | 132.345 | 723.493 | 1.2714 | 146.486 | 1 | 631.014 | 201.761 | 0 | 4.59 | 4.842 | 2853 | 0.9324 | 0.9479 | 4.682 | 2.1109 | 351.46 | 10.3685 | 114.456 | 12.74 | 17.8891 | 26.2754 | 697.218 | 1.115 | 152.358 | 1 | 618.274 | 83.4997 | 0 | 0 | 0 | 0.0227 | -0.0132 | -0.0321 | -0.0389 | -0.0154 | -0.0022 | -0.0281 | 0.0288 | 8.4126 | 0.1479 | 0 | 2.4676 | 0.9675 | 1740.65 | 0.2395 | 9238.36 | 0.1397 | 0.0013 | -0.0028 | 0 | 0.0001 | -0.0334 | 0 | -0.194 | 0.0577 | 0.0004 | -0.0001 | 0.0221 | -0.0042 | -0.0008 | -0.0013 | 0.0028 | 0.0148 | -0.0372 | 0 | 0 | 0 | 0 | 0.936 | 0 | 806.273 | 0.9905 | 58.823 | 0.6034 | 0.9754 | 6.5398 | 15.83 | 2.575 | 15.89 | 15.84 | 0.8089 | 2.854 | 0.4162 | 3.383 | -0.4731 | 0.7589 | 0.9966 | 2.3216 | 995.199 | 36.9578 | 89 | 173.7 | 122.5 | 56.2 | 219.768 | 0.2301 | 0 | 5.7 | 0.0049 | 0.0955 | 0.088 | 0.0493 | 0.0246 | 14.104 | 0 | 8.255 | 10.965 | 0.4136 | 0.0189 | 13.8354 | 0.35 | 0.086 | 0 | 0 | 2117 | 643 | 441 | 565 | 0.078 | 0.04 | 0.13 | 3 | 0.6 | 0.116 | 0.11 | 0.5811 | 0.0356 | 0.353 | 0.5535 | 0.353 | 0.8142 | 0.1764 | 1.065 | 0 | 0 | 18.27 | 0.475 | 10.81 | 15.84 | 0.1016 | 5.04 | 0 | 6.91 | 47.803 | 0 | 0 | 0 | 0 | 0 | 0 | 0.222 | 3.43 | 17.53 | 0.247 | 11.94 | 14.05 | 3.43 | 4.58 | 18.091 | 0.334 | 13.41 | 0 | 14.05 | 114.35 | 0 | 0.0604 | 0.0672 | 0.0355 | 0.0737 | 0.0903 | 0.0874 | 0.0998 | 0.0877 | 1.9062 | 0.0039 | 0 | 0.0903 | 0.0032 | 65.3582 | 0.0983 | 1046.2 | 0 | 0.0226 | 0.0203 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0067 | 0.0058 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0379 | 0 | 105.522 | 0.001 | 3.4843 | 0.0286 | 0.005 | 0.5536 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0333 | 29.099 | 2.8 | 24.0522 | 53.0949 | 40.5089 | 17.4008 | 83.5542 | 0.0767 | 0 | 1.8459 | 0.0012 | 0.0307 | 0.024 | 0.0167 | 0.0084 | 4.3345 | 0 | 2.3404 | 3.8913 | 0.1207 | 0.0063 | 4.2802 | 0.1 | 0.0251 | 0 | 0 | 1000.96 | 276.541 | 181.786 | 254.543 | 0.0339 | 0.0174 | 0.0578 | 0.9513 | 0.2028 | 0.0344 | 0.0353 | 0.211 | 0.0148 | 0.1513 | 0.1998 | 0.1513 | 0.3015 | 0.0698 | 0.4171 | 0 | 0 | 0 | 4.9162 | 0.1527 | 3.0709 | 5.1685 | 0.0349 | 1.6849 | 0 | 2.1646 | 14.0744 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0778 | 0.8887 | 5.6179 | 0.0725 | 3.4442 | 8.099 | 0.8887 | 1.1881 | 5.5104 | 0.0899 | 4.1816 | 0 | 3.7205 | 36.0395 | 0 | 0 | 0 | 0.0177 | 0.0296 | 0.0162 | 0.0345 | 0.0221 | 0.0423 | 0.0509 | 0.0505 | 0.7223 | 0.0013 | 0 | 0.0349 | 0.0011 | 23.0568 | 0.0293 | 375.025 | 0 | 0.0062 | 0.0048 | 0.0026 | 0.004 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0022 | 0.0019 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0153 | 0 | 39.0975 | 0.0003 | 1.1262 | 0.01 | 0.0019 | 0.1858 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0113 | 9.5342 | 0.8583 | 3.9873 | 5.7322 | 5.0409 | 2.5197 | 15.015 | 27.7464 | 0 | 5.5695 | 3.93 | 6.0381 | 326.152 | 467.576 | 2.5678 | 6.9791 | 0 | 91.3669 | 2.6365 | 4.1364 | 1.9544 | 7.2025 | 2.8088 | 6.1127 | 34.4004 | 23.8878 | 11.2651 | 97.3718 | 8.6069 | 2.258 | 4.2602 | 4.9342 | 24.1071 | 55.7395 | 3.1495 | 0.6667 | 0.3887 | 0.702 | 0.8615 | 0.71 | 1.2295 | 0.2042 | 0.8739 | 0 | 0 | 0 | 5.1876 | 4.7207 | 8.168 | 2.1894 | 7.9894 | 3.4406 | 0 | 1.0951 | 23.6929 | 0 | 0 | 0 | 0 | 0 | 0 | 4.7415 | 162.489 | 4.9878 | 2.3822 | 10.4319 | 110.283 | 19.1737 | 17.4307 | 2.5947 | 29.9535 | 8.8016 | 0 | 2.2725 | 136.947 | 0 | 266.153 | 509.091 | 110.678 | 189.46 | 586.364 | 0 | 355.793 | 304.514 | 22.6594 | 2.6373 | 0 | 3.6587 | 0.3268 | 3.7548 | 41.0596 | 11.3245 | 0 | 0 | 723.385 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 159.524 | 748.387 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4.0505 | 0 | 13.0876 | 0.0988 | 5.9234 | 4.734 | 0.5157 | 8.4653 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.4336 | 2.9239 | 7.5762 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 0.5051 | 404.356 | 72.04 | 0.1489 | 13.73 | 0.87 | 0.0686 | 5.4711 | 0.371 | 29.4773 | 3.3955 | 1.2077 | 0.9128 | 0.4697 | 0.0905 | 51.4535 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 541.904 | 2.4229 | 6.48 | 0.2027 | 2.2019 | 0.0597 | 1.1958 | 8.3645 | 0 | 0 | 0 | 0 | 0.501 | 0.0143 | 0.0042 | 2.8515 | 0.0342 | 0.0151 | 0.0052 | 44.0077 | -1 |
| 3058.88 | 2690.15 | 2248.9 | 1004.47 | 0.7884 | 100 | 106.24 | 0.1185 | 1.5153 | 0.0157 | 0.0007 | 0.9481 | 202.417 | 0 | 13.6872 | 408.402 | 9.6836 | 0.9687 | 192.733 | 12.5263 | 1.4092 | -5395.5 | 2551.75 | -3819.75 | -737 | 1.328 | 1.9893 | 7.3885 | 67.3 | 2.7889 | 0.2239 | 3.4588 | 83.8887 | 8.7289 | 50.4685 | 64.4021 | 49.5316 | 65.0665 | 86.7493 | 116.563 | 78.09 | 2.671 | 70 | 358.67 | 9.9271 | 142.294 | 745.688 | 0.9025 | 136.679 | 1 | 637.644 | 133.661 | 0 | 4.636 | 4.915 | 2865 | 0.9316 | 0.9433 | 4.6275 | 29.1309 | 360.138 | 9.8389 | 131.425 | 5.5936 | 10.8691 | 15.3094 | 730.378 | 0.9965 | 144.326 | 1 | 635.889 | 57.0841 | 0 | 0 | 0 | -0.0187 | -0.0594 | 0.0249 | 0.0041 | 0.0002 | -0.0765 | 0.0004 | 0.0086 | 6.2166 | 0.137 | 0 | 2.3466 | 0.9902 | 1826.11 | 0.2038 | 9117.37 | -0.0672 | -0.0028 | -0.0018 | 0 | 0.0002 | -0.0456 | 0 | -0.1188 | -0.0102 | 0.0003 | -0.0001 | -0.0086 | -0.0057 | 0.0001 | 0.0027 | 0.0017 | 0.1039 | -0.0866 | 0 | 0 | 0 | 0.465 | 0.9464 | 0 | 778.333 | 0.9902 | 59.0421 | 0.6039 | 0.9622 | 6.3241 | 15.78 | 2.27 | 15.86 | 15.8 | 0.7568 | 2.645 | 0.3273 | 3.442 | 0.7096 | 0.7863 | 0.9951 | 2.3437 | 992.83 | 40.5458 | 91 | 175.4 | 201.1 | 55.5 | 249.964 | 0.0577 | 0 | 7.56 | 0.0034 | 0.1027 | 0.0626 | 0.0463 | 0.0313 | 13.5649 | 0 | 19.388 | 14.952 | 1.3097 | 0.016 | 12.2552 | 0.48 | 0.0474 | 0 | 0 | 233 | 346 | 1429 | 807 | 0.161 | 0.142 | 0.11 | 1.9 | 1.1 | 0.073 | 0.385 | 0.8182 | 0.098 | 0.4235 | 0.7064 | 0.4236 | 0.9357 | 0.3062 | 0.22 | 0 | 0 | 13.92 | 0.393 | 14.09 | 37.242 | 0.0826 | 7.61 | 0 | 21.7 | 11.961 | 0 | 0 | 0 | 0 | 0 | 0 | 0.244 | 4.72 | 24.7 | 1.026 | 12.72 | 12.63 | 4.72 | 4.496 | 35.803 | 0.7151 | 17.14 | 0 | 28.89 | 73.632 | 0 | 0.0701 | 0.0529 | 0.1203 | 0.0517 | 0.0541 | 0.0989 | 0.0807 | 0.0378 | 7.5616 | 0.0035 | 0 | 0.0915 | 0.0005 | 126.103 | 0.0976 | 1222.1 | 0 | 0.0317 | 0.0235 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0045 | 0.0048 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0643 | 0.0155 | 0 | 128.763 | 0.0012 | 2.7835 | 0.0254 | 0.0259 | 0.442 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0331 | 27.861 | 2.9057 | 29.3966 | 74.695 | 65.5784 | 19.9839 | 92.8285 | 0.0216 | 0 | 2.7959 | 0.0008 | 0.0377 | 0.0166 | 0.014 | 0.0106 | 4.3027 | 0 | 5.6741 | 3.7801 | 0.3878 | 0.0054 | 4.0139 | 0.1286 | 0.0183 | 0 | 0 | 106.497 | 151.661 | 652.077 | 366.145 | 0.0663 | 0.0683 | 0.0513 | 0.5831 | 0.3444 | 0.0247 | 0.1352 | 0.3119 | 0.0433 | 0.1665 | 0.2588 | 0.1666 | 0.3539 | 0.1358 | 0.0937 | 0 | 0 | 0 | 4.8066 | 0.1337 | 3.83 | 10.9128 | 0.0247 | 2.7469 | 0 | 6.7634 | 3.3091 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0789 | 1.4892 | 6.7078 | 0.3503 | 3.2599 | 11.2226 | 1.4892 | 1.6179 | 10.2964 | 0.1827 | 4.958 | 0 | 8.0261 | 22.1485 | 0 | 0 | 0 | 0.0216 | 0.0221 | 0.0533 | 0.0211 | 0.0147 | 0.051 | 0.0345 | 0.0159 | 2.46 | 0.0011 | 0 | 0.0281 | 0.0002 | 39.4817 | 0.0302 | 376.413 | 0 | 0.0089 | 0.007 | 0.0067 | 0.0064 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0016 | 0.0017 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.009 | 0.0055 | 0 | 40.8608 | 0.0004 | 0.962 | 0.0078 | 0.0087 | 0.143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0102 | 10.8717 | 0.791 | 4.1681 | 5.7341 | 7.4754 | 2.4679 | 24.8852 | 7.321 | 0 | 7.116 | 2.8699 | 6.7774 | 399.362 | 0 | 3.306 | 6.7015 | 0 | 141.651 | 3.6611 | 13.525 | 1.6483 | 6.3586 | 3.8319 | 3.3651 | 4.3184 | 13.5593 | 37.4108 | 109.498 | 12.1235 | 7.1384 | 1.4888 | 2.8232 | 39.4422 | 32.6055 | 11.1311 | 0.9753 | 1.1227 | 0.8391 | 1.0969 | 0.8552 | 1.4381 | 0.353 | 0.1887 | 0 | 0 | 0 | 3.881 | 3.9589 | 9.902 | 4.9943 | 9.147 | 5.5678 | 0 | 3.4032 | 8.9488 | 0 | 0 | 0 | 0 | 0 | 0 | 5.2729 | 16.2027 | 6.8585 | 10.428 | 9.6785 | 225.794 | 43.4259 | 29.3676 | 4.902 | 71.7657 | 11.8759 | 0 | 4.5432 | 128.989 | 0 | 374.616 | 89.1323 | 484.105 | 0 | 0 | 129.239 | 0 | 440.816 | 121.636 | 2.5556 | 0 | 3.8989 | 0.0527 | 6.9056 | 47.8698 | 13.4041 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 79.1209 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 13.823 | 1.6426 | 0 | 16.5435 | 0.1232 | 4.7144 | 4.2075 | 2.6891 | 6.9889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.4141 | 2.8062 | 7.1665 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 0.6174 | 408.116 | 73.856 | 0.4455 | 15.97 | 0.76 | 0.1851 | 6.4786 | 0.3589 | 72.153 | 3.9131 | 1.029 | 0.9823 | 0.4232 | 0.0748 | 43.0771 | 265.09 | 0.5652 | 7.78 | 0.1334 | 3.2415 | 0.0486 | 2.9349 | 23.6052 | 493.005 | 2.2008 | 278.19 | 0.354 | 92.5866 | 0.126 | 56.4274 | 16.0862 | 0.0204 | 0.0194 | 0.0063 | 95.031 | 0.4984 | 0.0106 | 0.0034 | 2.1261 | 0.0204 | 0.0194 | 0.0063 | 95.031 | -1 |
| 2967.68 | 2600.47 | 2248.9 | 1004.47 | 0.7884 | 100 | 106.24 | 0.1185 | 1.5358 | 0.0111 | -0.0066 | 0.9494 | 202.454 | 0 | 12.6837 | 417.601 | 9.7046 | 0.9693 | 192.75 | 12.5263 | 1.4278 | -4196.5 | 2059.5 | -2948 | 622.75 | 0.683 | 1.323 | 2.2675 | 62.8 | 2.1444 | 0.1844 | 3.5067 | 85.4274 | 9.6234 | 50.4893 | 63.9315 | 49.5107 | 66.3322 | 86.9476 | 117.419 | 61.1 | 3.217 | 70 | 358.956 | 9.7842 | 142.701 | 745.413 | 1.1722 | 138.311 | 1 | 639.968 | 216.954 | 0 | 4.636 | 4.915 | 2865 | 0.9316 | 0.9433 | 4.6275 | 26.9791 | 358.347 | 9.8398 | 129.68 | 8.8612 | 13.0209 | 19.9475 | 725.465 | 0.9079 | 144.546 | 1 | 632.573 | 74.3992 | 0 | 0 | 0 | -0.0088 | -0.0523 | -0.0629 | 0.0067 | -0.0047 | -0.094 | -0.0251 | 0.0306 | 7.6346 | 0.137 | 0 | 2.2944 | 0.98 | 1788.86 | 0.1564 | 8615.27 | 0.001 | 0.0005 | -0.0033 | 0 | 0.0002 | -0.1279 | 0 | 0.1975 | 0.0791 | 0.0001 | 0.0001 | -0.0024 | -0.0048 | -0.0011 | -0.0005 | 0.0033 | -0.0299 | -0.1156 | 0 | 0 | 0 | 0.4642 | 0.9453 | 0 | 748.563 | 0.9906 | 58.7785 | 0.6054 | 0.9635 | 6.3354 | 15.78 | 2.27 | 15.86 | 15.8 | 0.7568 | 2.645 | 0.3273 | 3.442 | 0.7096 | 0.7863 | 0.9951 | 2.3437 | 992.83 | 40.5458 | 91 | 136.1 | 116.8 | 55.5 | 249.964 | 0.0577 | 0 | 7.56 | 0.0034 | 0.0945 | 0.0551 | 0.0415 | 0.0298 | 13.3953 | 0 | 7.245 | 16.973 | 1.3892 | 0.0151 | 12.0061 | 0.48 | 0.056 | 0 | 0 | 5781 | 2900 | 3961 | 948 | 0.912 | 1.766 | 3.039 | 2.4 | 0.6 | 0.071 | 0.091 | 0.5087 | 0.2885 | 0.4343 | 0.5245 | 0.4343 | 0.8582 | 0.247 | 0.226 | 0 | 0 | 12.48 | 0.36 | 11.45 | 31.969 | 0.1811 | 5.63 | 0 | 19.79 | 81.637 | 0 | 0 | 0 | 0 | 0 | 0 | 0.244 | 5.09 | 18.92 | 0.877 | 11.79 | 16.32 | 5.09 | 6.867 | 31.886 | 0.4077 | 7.18 | 0 | 25.3 | 90.715 | 0 | 0.0418 | 0.0555 | 0.0324 | 0.06 | 0.0293 | 0.081 | 0.0912 | 0.0476 | 2.8877 | 0.0035 | 0 | 0.0401 | 0.0287 | 100.511 | 0.0404 | 740.399 | 0 | 0.0331 | 0.0227 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0066 | 0.0042 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0306 | 0.0222 | 0 | 61.5139 | 0.0007 | 2.8729 | 0.0395 | 0.0199 | 0.4304 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0331 | 27.861 | 2.9057 | 29.3966 | 53.8333 | 44.2335 | 19.9839 | 92.8285 | 0.0216 | 0 | 2.7959 | 0.0008 | 0.0327 | 0.0159 | 0.0128 | 0.0101 | 4.2453 | 0 | 2.277 | 3.9049 | 0.4127 | 0.0051 | 3.9363 | 0.1286 | 0.0174 | 0 | 0 | 2803.16 | 1377.76 | 1965.46 | 423.479 | 0.4553 | 0.882 | 1.5118 | 0.7583 | 0.2186 | 0.0234 | 0.0298 | 0.218 | 0.1153 | 0.1588 | 0.2266 | 0.1588 | 0.328 | 0.0908 | 0.1009 | 0 | 0 | 0 | 4.3824 | 0.1203 | 3.0596 | 9.2406 | 0.0441 | 1.6988 | 0 | 5.5396 | 21.5711 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0789 | 1.5156 | 5.1862 | 0.3266 | 3.4278 | 8.7793 | 1.5156 | 2.1256 | 9.6503 | 0.1204 | 2.7826 | 0 | 7.1398 | 30.9028 | 0 | 0 | 0 | 0.0103 | 0.0248 | 0.014 | 0.0282 | 0.0089 | 0.0426 | 0.0453 | 0.021 | 1.0533 | 0.0011 | 0 | 0.0134 | 0.01 | 35.7156 | 0.0127 | 205.529 | 0 | 0.0077 | 0.0072 | 0.0064 | 0.0064 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0022 | 0.0016 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0056 | 0.0069 | 0 | 20.5522 | 0.0002 | 1.0021 | 0.0122 | 0.0064 | 0.1432 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0102 | 10.8717 | 0.791 | 4.1681 | 4.5861 | 4.4915 | 2.4679 | 24.8852 | 7.321 | 0 | 7.116 | 2.8699 | 6.153 | 496.396 | 624.06 | 3.1427 | 6.6164 | 0 | 57.1204 | 4.0644 | 14.3147 | 1.5571 | 6.2289 | 3.8319 | 3.9248 | 137.758 | 140.811 | 134.362 | 152.228 | 133.529 | 133.484 | 134.024 | 3.8217 | 27.9793 | 38.494 | 2.5951 | 0.5955 | 2.9979 | 0.8602 | 0.8204 | 0.8772 | 1.2938 | 0.2841 | 0.1925 | 0 | 0 | 0 | 3.4767 | 3.6794 | 8.0238 | 4.2888 | 15.4539 | 4.0705 | 0 | 3.0923 | 37.6287 | 0 | 0 | 0 | 0 | 0 | 0 | 5.2729 | 18.8665 | 5.2798 | 8.9128 | 9.0916 | 184.174 | 39.091 | 34.4251 | 4.3952 | 44.9089 | 4.9673 | 0 | 3.9995 | 121.93 | 0 | 477.033 | 106.169 | 51.4694 | 892.193 | 616.842 | 86.1931 | 364.072 | 155.683 | 37.8245 | 2.5556 | 0 | 1.7466 | 2.9308 | 5.6187 | 25.8449 | 8.594 | 0 | 0 | 686.578 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 138.583 | 395.294 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6.5964 | 2.3441 | 0 | 8.2176 | 0.0727 | 4.8876 | 6.5231 | 2.0667 | 6.7934 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.4141 | 2.8062 | 7.1665 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 0.671 | 408.468 | 74.016 | 0.3469 | 17.54 | 1.36 | 0.1534 | 8.2095 | 0.5478 | 51.7053 | 4.2941 | 1.8374 | 0.9651 | 0.1343 | 0.0391 | 13.9158 | 265.184 | 0.6286 | 6.28 | 0.1145 | 2.2928 | 0.0417 | 2.3682 | 18.212 | 535.182 | 2.217 | 7.09 | 0.3168 | 2.4902 | 0.0878 | 1.3248 | 14.2892 | 0.0111 | 0.0124 | 0.0045 | 111.653 | 0.4993 | 0.0172 | 0.0046 | 3.4456 | 0.0111 | 0.0124 | 0.0045 | 111.653 | -1 |
df.pca.varimp(use_pandas=True)
| pc1 | pc2 | pc3 | pc4 | pc5 | pc6 | pc7 | pc8 | pc9 | ... | pc41 | pc42 | pc43 | pc44 | pc45 | pc46 | pc47 | pc48 | pc49 | pc50 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Standard deviation | 15109.664970 | 6725.342943 | 4413.131230 | 2870.264991 | 1498.195772 | 1174.226423 | 1069.430682 | 683.967834 | 539.561631 | ... | 105.901247 | 103.321398 | 102.225876 | 98.041429 | 92.402485 | 89.151358 | 84.137627 | 72.015635 | 70.179948 | 68.303435 |
| 1 | Proportion of Variance | 0.737682 | 0.146146 | 0.062929 | 0.026620 | 0.007253 | 0.004455 | 0.003695 | 0.001512 | 0.000941 | ... | 0.000036 | 0.000034 | 0.000034 | 0.000031 | 0.000028 | 0.000026 | 0.000023 | 0.000017 | 0.000016 | 0.000015 |
| 2 | Cumulative Proportion | 0.737682 | 0.883828 | 0.946757 | 0.973377 | 0.980630 | 0.985085 | 0.988780 | 0.990292 | 0.991233 | ... | 0.999621 | 0.999656 | 0.999690 | 0.999721 | 0.999748 | 0.999774 | 0.999797 | 0.999814 | 0.999829 | 0.999845 |
3 rows × 51 columns
df_new = df.pca.predict(df)
pca prediction progress: |███████████████████████████████████████████████████████| (done) 100%
from h2o.estimators.naive_bayes import H2ONaiveBayesEstimator
nv = H2ONaiveBayesEstimator()
df_new = df_new.cbind(df[response])
df_new
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | PC11 | PC12 | PC13 | PC14 | PC15 | PC16 | PC17 | PC18 | PC19 | PC20 | PC21 | PC22 | PC23 | PC24 | PC25 | PC26 | PC27 | PC28 | PC29 | PC30 | PC31 | PC32 | PC33 | PC34 | PC35 | PC36 | PC37 | PC38 | PC39 | PC40 | PC41 | PC42 | PC43 | PC44 | PC45 | PC46 | PC47 | PC48 | PC49 | PC50 | C591 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| -592.924 | 20.9172 | 110.389 | -29.7802 | 182.517 | 487.758 | -193.233 | 462.334 | 340.492 | -130.889 | 472.145 | -480.984 | -114.114 | 1102.51 | -304.477 | 1569.31 | 381.834 | 378.569 | -255.548 | -788.67 | 379.957 | -798.984 | -1713.4 | -140.72 | 605.984 | -1011.06 | 792.478 | -2060.34 | -562.717 | 618.011 | -3830 | -4548.31 | -2389.48 | 1802.55 | 1276.43 | -1835.03 | 452.319 | -1053.15 | 738.011 | 75.3505 | 135.53 | -121.195 | 184.724 | -193.295 | -46.5973 | 210.84 | -74.0155 | 9.57148 | -51.333 | -76.9356 | nan |
| -11534.5 | -5286.1 | -3786.98 | -636.458 | 85.7539 | 328.37 | 127.425 | -46.5265 | 32.0369 | 351.168 | 334.631 | -715.97 | -391.275 | -51.6809 | 140.335 | -341.925 | -216.37 | 10.1352 | 39.9204 | -432.827 | 112.051 | -410.095 | 458.89 | -336.965 | -285.354 | -233.58 | -2.49093 | 160.054 | -306.804 | -286.891 | -158.937 | -17.3166 | 112.96 | -55.6624 | -94.9872 | 20.6565 | 113.859 | -95.7309 | -132.402 | 26.6555 | 129.985 | 94.5545 | 65.3003 | -59.6731 | -0.814107 | 50.6721 | -97.9126 | 86.1044 | 12.8567 | -77.8273 | -1 |
| -12386.1 | -1929.82 | -4272.17 | 1543.52 | 167.491 | -479.344 | -382.873 | -48.7234 | -40.3133 | -334.318 | 43.2105 | -885.859 | -554.415 | 65.627 | 403.3 | -513.742 | 47.7638 | -29.8757 | -123.607 | -113.843 | -41.9001 | 306.906 | -365.023 | 51.2061 | -388.75 | 289.237 | 322.123 | -0.160722 | -20.3228 | -291.55 | -16.859 | 88.0648 | -41.7782 | 38.299 | -20.4993 | -43.2778 | 102.506 | -136.904 | 25.6039 | -9.48559 | 231.368 | 159.183 | 117.707 | 175.424 | -108.203 | -89.194 | -111.213 | 76.3213 | 10.3245 | -38.4613 | -1 |
| -12561.3 | -3499.87 | -4118.21 | 1909.03 | 264.268 | -331.683 | 237.089 | -24.8371 | -88.8476 | 187.667 | 386.752 | 342.802 | 42.3286 | -167.799 | 8.87365 | -275.71 | -169.308 | -284.688 | 65.8783 | -284.725 | 453.833 | 40.2166 | 373.444 | -141.334 | -25.1994 | 144.003 | -117.534 | -152.19 | 232.582 | -44.6192 | 41.8081 | -101.429 | -64.1309 | -1.23436 | 69.9953 | -77.9073 | 79.3531 | 93.3953 | -7.53619 | -6.34854 | 45.1135 | -24.9542 | 27.3692 | 18.5816 | 41.3584 | 66.8851 | 67.0736 | 14.2028 | 3.23575 | -49.1827 | 1 |
| -13386.7 | -2856.94 | -1133.31 | 1537.09 | -669.983 | 152.871 | 295.298 | -62.9468 | 37.6003 | 59.3502 | -489.561 | 74.08 | -10.2971 | 144.643 | 207.927 | -34.9018 | 25.1381 | 88.0423 | 634.964 | 165.586 | -54.6295 | 37.3927 | 362.445 | 19.2126 | -126.133 | 276.847 | -212.34 | -196.67 | -74.356 | 171.345 | -80.0471 | 11.9357 | -108.963 | 46.8753 | -7.61565 | -147.59 | 109.023 | 90.9229 | -56.9452 | 5.73932 | -4.55311 | -14.7403 | 33.3267 | -2.51454 | 25.3325 | 55.8882 | 72.3886 | 17.8731 | 11.0149 | -23.4201 | -1 |
| -12398.1 | -4378.88 | -3097.15 | -89.7461 | 83.1411 | -299.545 | 211.469 | -57.8647 | -53.1706 | -187.896 | 27.9401 | -264.321 | -190.464 | 154.113 | 449.827 | -282.093 | 261.975 | 111.253 | -454.552 | 241.832 | 111.385 | 131.423 | -370.547 | 414.939 | 46.1 | 164.563 | 42.8768 | 366.746 | -306.135 | -261.887 | -47.8089 | -20.2831 | -89.4125 | 9.78995 | -66.4182 | -14.3769 | -4.33917 | -25.6912 | -22.7031 | 31.4315 | 149.71 | 120.23 | 81.1472 | -18.8675 | -77.6879 | -14.7192 | -109.961 | 30.2508 | -30.3718 | 29.3928 | -1 |
| -11450.2 | -4241.94 | -4378.96 | -122.854 | -44.2847 | 1512.77 | -628.914 | -16.7816 | 39.4811 | 134.671 | -348.067 | -172.743 | -56.8033 | -159.396 | 77.5129 | -51.9263 | 414.937 | -486.745 | -463.898 | 332.989 | -201.626 | -184.524 | -409.501 | 286.284 | 86.53 | -293.129 | -104.899 | -115.317 | 506.453 | -343.57 | -377.607 | 265.119 | 59.1057 | -81.7089 | 112.454 | 103.436 | 105.061 | -40.5023 | -2.05816 | 13.916 | 51.4149 | 36.7245 | 45.0155 | -71.0542 | -60.9575 | 24.8618 | 79.9687 | -3.41274 | -38.9272 | 27.3081 | -1 |
| -11937.6 | -5222.16 | -4625.32 | -465.893 | 622.595 | 1048.54 | -94.6231 | -37.2258 | -43.1341 | -176.156 | -531.141 | -17.0111 | 41.7439 | -400.215 | -193.333 | 311.245 | 650.347 | -383.646 | 119.413 | -110.392 | 92.0592 | -84.115 | 87.3008 | 31.3468 | -299.536 | -227.681 | 5.16869 | 51.6454 | 145.123 | -123.469 | 36.746 | -136.348 | 145.341 | 185.126 | -243.689 | 73.436 | -62.2074 | 43.1725 | -4.92213 | 21.1817 | 175.377 | 102.209 | 61.3867 | -81.9159 | 23.5855 | 40.0074 | -86.2752 | 2.39277 | 15.7187 | 13.5415 | -1 |
| -11905.5 | -4832.04 | -3377.28 | 794.797 | 160.113 | -789.836 | 176.925 | -53.6715 | 4.95713 | 68.3563 | -100.718 | -139.059 | -82.7575 | 341.443 | 250.921 | -454.672 | -391.579 | -68.9291 | 248.535 | 202.742 | -145.306 | -109.742 | 121.099 | -82.9172 | -295.795 | 22.3287 | -376.844 | 88.1667 | -255.921 | 103.292 | -63.7711 | -122.385 | -130.851 | 43.2896 | -2.72734 | -106.896 | -129.244 | -18.8196 | -117.949 | 1.27492 | 40.0081 | -47.529 | 62.0492 | 15.382 | 142.786 | -186.786 | 90.4379 | -78.2394 | -1.32889 | 90.3875 | -1 |
| -12315.6 | -5060.56 | -410.41 | -558.746 | 2967.12 | 5492.33 | 688.898 | 7.27391 | 90.8239 | 452.116 | -224.883 | 284.151 | 191.291 | 41.5019 | 173.758 | 399.503 | 439.124 | -124.056 | 117.541 | -81.9306 | -56.2858 | -223.662 | -37.1356 | -79.6341 | -256.007 | -161.577 | -250.689 | -98.7033 | 298.746 | -730.282 | -100.223 | 37.0707 | -6.38875 | -25.2979 | 80.205 | 49.8801 | -105.942 | 90.1094 | 53.9556 | 14.8581 | 30.2233 | -32.9396 | 16.0849 | 8.75086 | -8.81606 | 48.1785 | 100.275 | 33.2011 | -8.89236 | -13.6649 | -1 |
h2o.download_csv(df_new,"C:\\Users\\Admin\\Desktop\\FMT")
'C:\\Users\\Admin\\Desktop\\FMT\\unknown'
pca_df = pd.read_csv('PCA_OD.csv')
print(pca_df.shape)
pca_df.head()
(1568, 51)
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | ... | PC42 | PC43 | PC44 | PC45 | PC46 | PC47 | PC48 | PC49 | PC50 | C591 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | -592.924304 | 20.917196 | 110.389292 | -29.780230 | 182.517317 | 487.757737 | -193.233225 | 462.333997 | 340.492422 | -130.888968 | ... | -121.195286 | 184.723652 | -193.295096 | -46.597260 | 210.840342 | -74.015457 | 9.571485 | -51.333020 | -76.935605 | -1 |
| 1 | -11534.534860 | -5286.104909 | -3786.984314 | -636.457862 | 85.753879 | 328.369646 | 127.425188 | -46.526547 | 32.036950 | 351.167986 | ... | 94.554459 | 65.300338 | -59.673060 | -0.814107 | 50.672109 | -97.912562 | 86.104438 | 12.856700 | -77.827252 | -1 |
| 2 | -12386.084860 | -1929.815775 | -4272.166834 | 1543.516825 | 167.490946 | -479.343759 | -382.872794 | -48.723428 | -40.313318 | -334.317904 | ... | 159.183024 | 117.706921 | 175.423993 | -108.203004 | -89.194043 | -111.213116 | 76.321301 | 10.324508 | -38.461348 | -1 |
| 3 | -12561.346130 | -3499.871039 | -4118.211872 | 1909.034331 | 264.268464 | -331.682796 | 237.089044 | -24.837079 | -88.847628 | 187.667223 | ... | -24.954219 | 27.369188 | 18.581551 | 41.358416 | 66.885104 | 67.073605 | 14.202763 | 3.235745 | -49.182694 | 1 |
| 4 | -13386.666180 | -2856.942202 | -1133.308163 | 1537.090339 | -669.983465 | 152.870526 | 295.297500 | -62.946769 | 37.600294 | 59.350230 | ... | -14.740262 | 33.326744 | -2.514542 | 25.332467 | 55.888198 | 72.388642 | 17.873116 | 11.014890 | -23.420128 | -1 |
5 rows × 51 columns
pca_df2= pca_df.drop('C591', axis=1)
pca_df2.head()
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | ... | PC41 | PC42 | PC43 | PC44 | PC45 | PC46 | PC47 | PC48 | PC49 | PC50 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | -592.924304 | 20.917196 | 110.389292 | -29.780230 | 182.517317 | 487.757737 | -193.233225 | 462.333997 | 340.492422 | -130.888968 | ... | 135.530242 | -121.195286 | 184.723652 | -193.295096 | -46.597260 | 210.840342 | -74.015457 | 9.571485 | -51.333020 | -76.935605 |
| 1 | -11534.534860 | -5286.104909 | -3786.984314 | -636.457862 | 85.753879 | 328.369646 | 127.425188 | -46.526547 | 32.036950 | 351.167986 | ... | 129.984577 | 94.554459 | 65.300338 | -59.673060 | -0.814107 | 50.672109 | -97.912562 | 86.104438 | 12.856700 | -77.827252 |
| 2 | -12386.084860 | -1929.815775 | -4272.166834 | 1543.516825 | 167.490946 | -479.343759 | -382.872794 | -48.723428 | -40.313318 | -334.317904 | ... | 231.367742 | 159.183024 | 117.706921 | 175.423993 | -108.203004 | -89.194043 | -111.213116 | 76.321301 | 10.324508 | -38.461348 |
| 3 | -12561.346130 | -3499.871039 | -4118.211872 | 1909.034331 | 264.268464 | -331.682796 | 237.089044 | -24.837079 | -88.847628 | 187.667223 | ... | 45.113478 | -24.954219 | 27.369188 | 18.581551 | 41.358416 | 66.885104 | 67.073605 | 14.202763 | 3.235745 | -49.182694 |
| 4 | -13386.666180 | -2856.942202 | -1133.308163 | 1537.090339 | -669.983465 | 152.870526 | 295.297500 | -62.946769 | 37.600294 | 59.350230 | ... | -4.553109 | -14.740262 | 33.326744 | -2.514542 | 25.332467 | 55.888198 | 72.388642 | 17.873116 | 11.014890 | -23.420128 |
5 rows × 50 columns
y = pca_df['C591']
X = pca_df2
classifier = Classification(
predictor='svm',
params= {},
cv_folds=2,
epochs=5)
classifier.fit(X, y)
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Started LuciferML
Checking if labels or features are categorical! [*]
Features are not categorical [ ✓ ]
Labels are not categorical [ ✓ ]
Checking for Categorical Variables Done [ ✓ ]
Checking for Sparse Matrix [*]
Splitting Data into Train and Validation Sets [*]
Splitting Done [ ✓ ]
Scaling Training and Test Sets [*]
Scaling Done [ ✓ ]
Training Support Vector Machine on Training Set [*]
Model Training Done [ ✓ ]
Predicting Data [*]
Data Prediction Done [ ✓ ]
Making Confusion Matrix [*]
[[289 0]
[ 25 0]]
Confusion Matrix Done [ ✓ ] Evaluating Model Performance [*] Validation Accuracy is : 0.9203821656050956 Evaluating Model Performance [ ✓ ] Applying K-Fold Cross Validation [*] Accuracy: 93.70 % Standard Deviation: 0.08 % K-Fold Cross Validation [ ✓ ] Complete [ ✓ ] Time Elapsed : 0.9894187450408936 seconds
from h2o.estimators.pca import H2OPrincipalComponentAnalysisEstimator
df2 = h2o.import_file("C:\\Users\\Admin\\Desktop\\FMT\\OS.csv")
df2.pca = H2OPrincipalComponentAnalysisEstimator(k=70)
df2
Parse progress: |████████████████████████████████████████████████████████████████| (done) 100%
| C1 | C2 | C3 | C4 | C5 | C6 | C7 | C8 | C9 | C10 | C11 | C12 | C13 | C14 | C15 | C16 | C17 | C18 | C19 | C20 | C21 | C22 | C23 | C24 | C25 | C26 | C27 | C28 | C29 | C30 | C31 | C32 | C33 | C34 | C35 | C36 | C37 | C38 | C39 | C40 | C41 | C42 | C43 | C44 | C45 | C46 | C47 | C48 | C49 | C50 | C51 | C52 | C53 | C54 | C55 | C56 | C57 | C58 | C59 | C60 | C61 | C62 | C63 | C64 | C65 | C66 | C67 | C68 | C69 | C70 | C71 | C72 | C73 | C74 | C75 | C76 | C77 | C78 | C79 | C80 | C81 | C82 | C83 | C84 | C85 | C86 | C87 | C88 | C89 | C90 | C91 | C92 | C93 | C94 | C95 | C96 | C97 | C98 | C99 | C100 | C101 | C102 | C103 | C104 | C105 | C106 | C107 | C108 | C109 | C110 | C111 | C112 | C113 | C114 | C115 | C116 | C117 | C118 | C119 | C120 | C121 | C122 | C123 | C124 | C125 | C126 | C127 | C128 | C129 | C130 | C131 | C132 | C133 | C134 | C135 | C136 | C137 | C138 | C139 | C140 | C141 | C142 | C143 | C144 | C145 | C146 | C147 | C148 | C149 | C150 | C151 | C152 | C153 | C154 | C155 | C156 | C157 | C158 | C159 | C160 | C161 | C162 | C163 | C164 | C165 | C166 | C167 | C168 | C169 | C170 | C171 | C172 | C173 | C174 | C175 | C176 | C177 | C178 | C179 | C180 | C181 | C182 | C183 | C184 | C185 | C186 | C187 | C188 | C189 | C190 | C191 | C192 | C193 | C194 | C195 | C196 | C197 | C198 | C199 | C200 | C201 | C202 | C203 | C204 | C205 | C206 | C207 | C208 | C209 | C210 | C211 | C212 | C213 | C214 | C215 | C216 | C217 | C218 | C219 | C220 | C221 | C222 | C223 | C224 | C225 | C226 | C227 | C228 | C229 | C230 | C231 | C232 | C233 | C234 | C235 | C236 | C237 | C238 | C239 | C240 | C241 | C242 | C243 | C244 | C245 | C246 | C247 | C248 | C249 | C250 | C251 | C252 | C253 | C254 | C255 | C256 | C257 | C258 | C259 | C260 | C261 | C262 | C263 | C264 | C265 | C266 | C267 | C268 | C269 | C270 | C271 | C272 | C273 | C274 | C275 | C276 | C277 | C278 | C279 | C280 | C281 | C282 | C283 | C284 | C285 | C286 | C287 | C288 | C289 | C290 | C291 | C292 | C293 | C294 | C295 | C296 | C297 | C298 | C299 | C300 | C301 | C302 | C303 | C304 | C305 | C306 | C307 | C308 | C309 | C310 | C311 | C312 | C313 | C314 | C315 | C316 | C317 | C318 | C319 | C320 | C321 | C322 | C323 | C324 | C325 | C326 | C327 | C328 | C329 | C330 | C331 | C332 | C333 | C334 | C335 | C336 | C337 | C338 | C339 | C340 | C341 | C342 | C343 | C344 | C345 | C346 | C347 | C348 | C349 | C350 | C351 | C352 | C353 | C354 | C355 | C356 | C357 | C358 | C359 | C360 | C361 | C362 | C363 | C364 | C365 | C366 | C367 | C368 | C369 | C370 | C371 | C372 | C373 | C374 | C375 | C376 | C377 | C378 | C379 | C380 | C381 | C382 | C383 | C384 | C385 | C386 | C387 | C388 | C389 | C390 | C391 | C392 | C393 | C394 | C395 | C396 | C397 | C398 | C399 | C400 | C401 | C402 | C403 | C404 | C405 | C406 | C407 | C408 | C409 | C410 | C411 | C412 | C413 | C414 | C415 | C416 | C417 | C418 | C419 | C420 | C421 | C422 | C423 | C424 | C425 | C426 | C427 | C428 | C429 | C430 | C431 | C432 | C433 | C434 | C435 | C436 | C437 | C438 | C439 | C440 | C441 | C442 | C443 | C444 | C445 | C446 | C447 | C448 | C449 | C450 | C451 | C452 | C453 | C454 | C455 | C456 | C457 | C458 | C459 | C460 | C461 | C462 | C463 | C464 | C465 | C466 | C467 | C468 | C469 | C470 | C471 | C472 | C473 | C474 | C475 | C476 | C477 | C478 | C479 | C480 | C481 | C482 | C483 | C484 | C485 | C486 | C487 | C488 | C489 | C490 | C491 | C492 | C493 | C494 | C495 | C496 | C497 | C498 | C499 | C500 | C501 | C502 | C503 | C504 | C505 | C506 | C507 | C508 | C509 | C510 | C511 | C512 | C513 | C514 | C515 | C516 | C517 | C518 | C519 | C520 | C521 | C522 | C523 | C524 | C525 | C526 | C527 | C528 | C529 | C530 | C531 | C532 | C533 | C534 | C535 | C536 | C537 | C538 | C539 | C540 | C541 | C542 | C543 | C544 | C545 | C546 | C547 | C548 | C549 | C550 | C551 | C552 | C553 | C554 | C555 | C556 | C557 | C558 | C559 | C560 | C561 | C562 | C563 | C564 | C565 | C566 | C567 | C568 | C569 | C570 | C571 | C572 | C573 | C574 | C575 | C576 | C577 | C578 | C579 | C580 | C581 | C582 | C583 | C584 | C585 | C586 | C587 | C588 | C589 | C590 | C591 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| nan | 0 | 1 | 10 | 100 | 101 | 102 | 103 | 104 | 105 | 106 | 107 | 108 | 109 | 11 | 110 | 111 | 112 | 113 | 114 | 115 | 116 | 117 | 118 | 119 | 12 | 120 | 121 | 122 | 123 | 124 | 125 | 126 | 127 | 128 | 129 | 13 | 130 | 131 | 132 | 133 | 134 | 135 | 136 | 137 | 138 | 139 | 14 | 140 | 141 | 142 | 143 | 144 | 145 | 146 | 147 | 148 | 149 | 15 | 150 | 151 | 152 | 153 | 154 | 155 | 156 | 157 | 158 | 159 | 16 | 160 | 161 | 162 | 163 | 164 | 165 | 166 | 167 | 168 | 169 | 17 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | 179 | 18 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | 187 | 188 | 189 | 19 | 190 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | 2 | 20 | 200 | 201 | 202 | 203 | 204 | 205 | 206 | 207 | 208 | 209 | 21 | 210 | 211 | 212 | 213 | 214 | 215 | 216 | 217 | 218 | 219 | 22 | 220 | 221 | 222 | 223 | 224 | 225 | 226 | 227 | 228 | 229 | 23 | 230 | 231 | 232 | 233 | 234 | 235 | 236 | 237 | 238 | 239 | 24 | 240 | 241 | 242 | 243 | 244 | 245 | 246 | 247 | 248 | 249 | 25 | 250 | 251 | 252 | 253 | 254 | 255 | 256 | 257 | 258 | 259 | 26 | 260 | 261 | 262 | 263 | 264 | 265 | 266 | 267 | 268 | 269 | 27 | 270 | 271 | 272 | 273 | 274 | 275 | 276 | 277 | 278 | 279 | 28 | 280 | 281 | 282 | 283 | 284 | 285 | 286 | 287 | 288 | 289 | 29 | 290 | 291 | 292 | 293 | 294 | 295 | 296 | 297 | 298 | 299 | 3 | 30 | 300 | 301 | 302 | 303 | 304 | 305 | 306 | 307 | 308 | 309 | 31 | 310 | 311 | 312 | 313 | 314 | 315 | 316 | 317 | 318 | 319 | 32 | 320 | 321 | 322 | 323 | 324 | 325 | 326 | 327 | 328 | 329 | 33 | 330 | 331 | 332 | 333 | 334 | 335 | 336 | 337 | 338 | 339 | 34 | 340 | 341 | 342 | 343 | 344 | 345 | 346 | 347 | 348 | 349 | 35 | 350 | 351 | 352 | 353 | 354 | 355 | 356 | 357 | 358 | 359 | 36 | 360 | 361 | 362 | 363 | 364 | 365 | 366 | 367 | 368 | 369 | 37 | 370 | 371 | 372 | 373 | 374 | 375 | 376 | 377 | 378 | 379 | 38 | 380 | 381 | 382 | 383 | 384 | 385 | 386 | 387 | 388 | 389 | 39 | 390 | 391 | 392 | 393 | 394 | 395 | 396 | 397 | 398 | 399 | 4 | 40 | 400 | 401 | 402 | 403 | 404 | 405 | 406 | 407 | 408 | 409 | 41 | 410 | 411 | 412 | 413 | 414 | 415 | 416 | 417 | 418 | 419 | 42 | 420 | 421 | 422 | 423 | 424 | 425 | 426 | 427 | 428 | 429 | 43 | 430 | 431 | 432 | 433 | 434 | 435 | 436 | 437 | 438 | 439 | 44 | 440 | 441 | 442 | 443 | 444 | 445 | 446 | 447 | 448 | 449 | 45 | 450 | 451 | 452 | 453 | 454 | 455 | 456 | 457 | 458 | 459 | 46 | 460 | 461 | 462 | 463 | 464 | 465 | 466 | 467 | 468 | 469 | 47 | 470 | 471 | 472 | 473 | 474 | 475 | 476 | 477 | 478 | 479 | 48 | 480 | 481 | 482 | 483 | 484 | 485 | 486 | 487 | 488 | 489 | 49 | 490 | 491 | 492 | 493 | 494 | 495 | 496 | 497 | 498 | 499 | 5 | 50 | 500 | 501 | 502 | 503 | 504 | 505 | 506 | 507 | 508 | 509 | 51 | 510 | 511 | 512 | 513 | 514 | 515 | 516 | 517 | 518 | 519 | 52 | 520 | 521 | 522 | 523 | 524 | 525 | 526 | 527 | 528 | 529 | 53 | 530 | 531 | 532 | 533 | 534 | 535 | 536 | 537 | 538 | 539 | 54 | 540 | 541 | 542 | 543 | 544 | 545 | 546 | 547 | 548 | 549 | 55 | 550 | 551 | 552 | 553 | 554 | 555 | 556 | 557 | 558 | 559 | 56 | 560 | 561 | 562 | 563 | 564 | 565 | 566 | 567 | 568 | 569 | 57 | 570 | 571 | 572 | 573 | 574 | 575 | 576 | 577 | 578 | 579 | 58 | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | 59 | 6 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 7 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 8 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 9 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 |
| 1 | 2992.4 | 2467.07 | 0.0006 | 0 | 0 | 0.0132 | -0.0052 | -0.0005 | 0.0015 | -0.0007 | -0.1275 | -0.1515 | 0 | 0.9549 | 0 | 0 | 0.4687 | 0.9481 | 0 | 781.541 | 0.9641 | 57.887 | 0.5988 | 0.9589 | 199.678 | 6.4276 | 15.78 | 3.62 | 15.83 | 15.83 | 0.9933 | 2.914 | 0.6314 | 3.361 | 0.0473 | 0 | 0.7509 | 0.9969 | 2.3532 | 1006.41 | 44.814 | 92 | 162 | 144.3 | 70.3999 | 774.816 | 7.6212 | 0.6112 | 0 | 8.1 | 0.0051 | 0.1061 | 0.0666 | 0.0871 | 0.021 | 9.8675 | 0 | 395.572 | 3.617 | 6.156 | 0.4659 | 0.0122 | 9.4016 | 0.3 | 0.0562 | 0 | 0 | 5480 | 10.1679 | 3218 | 3986 | 1104 | 0.895 | 1.801 | 2.98 | 3.2 | 1 | 0.111 | 0.073 | 0.972 | 0.4277 | 0.1036 | 0.2468 | 0.4883 | 0.2468 | 0.6791 | 0.2985 | 1.081 | 0 | 0 | 189.51 | 12.1 | 0.409 | 11.19 | 21.486 | 0.1668 | 5.89 | 0 | 13.04 | 48.896 | 0 | 12.4659 | 0 | 0 | 0 | 0 | 0 | 0.08 | 7.92 | 22.9 | 1.033 | 5.75 | 2191.67 | 1.4033 | 15.66 | 7.92 | 12.275 | 20.533 | 0.2948 | 19.65 | 0 | 15.66 | 72.05 | 0 | -2609.25 | 0.1176 | 0.0898 | 0.0508 | 0.0802 | 0.0532 | 0.108 | 0.0565 | 0.0241 | 4.9126 | 0.0031 | 1505.5 | 0 | 0.0496 | 0.001 | 106.537 | 0.038 | 1249.3 | 0 | 0.0175 | 0.0192 | 0 | -1941.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0061 | 0.0044 | 502 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0461 | 0.0182 | 0 | 0.438 | 146.455 | 0.0043 | 2.0666 | 0.0408 | 0.0242 | 0.3887 | 0 | 0 | 0 | 0 | 0.8925 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0437 | 21.357 | 4.0441 | 1.4817 | 24.2871 | 60.0743 | 55.5934 | 24.1213 | 244.067 | 0.1968 | 0 | 3.1604 | 0.0013 | 0.0314 | 62.7556 | 0.0208 | 0.0243 | 0.0069 | 3.1449 | 0 | 1.2138 | 2.1656 | 0.1337 | 0.004 | 3.0255 | 2.7889 | 0.0675 | 0.0183 | 0 | 0 | 3020.46 | 1746.6 | 2243.43 | 585.382 | 0.506 | 1.0307 | 1107.43 | 0.2252 | 1.711 | 1.1035 | 0.3018 | 0.0323 | 0.0253 | 0.1537 | 0.0449 | 0.0993 | 0.1867 | 0.0993 | 3.4822 | 0.261 | 0.1125 | 0.4542 | 0 | 0 | 0 | 4.1373 | 0.115 | 3.3804 | 5.9438 | 85.6039 | 0.0577 | 1.9145 | 0 | 3.9535 | 17.601 | 0 | 0 | 0 | 0 | 0 | 8.7588 | 0 | 0.0224 | 2.1534 | 8.0936 | 0.3593 | 1.8504 | 11.0676 | 2.1534 | 3.0739 | 6.3113 | 50.179 | 0.0874 | 6.1589 | 0 | 5.0662 | 18.8217 | 5.131 | 4.6735 | 0 | 0.0259 | 0.0418 | 64.1668 | 0.0281 | 0.0381 | 0.0173 | 0.0547 | 0.0231 | 0.0102 | 1.622 | 0.0011 | 0 | 0.0145 | 49.821 | 0.0003 | 32.0989 | 0.0124 | 504.083 | 0 | 0.0055 | 0.0052 | 0.0026 | 0.0026 | 0 | 66.6948 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0018 | 0.0013 | 0 | 0 | 88.3548 | 0 | 0 | 0 | 0 | 0 | 0.0108 | 0.0068 | 0 | 55.3223 | 0.0013 | 118.67 | 0.6917 | 0.0123 | 0.0095 | 0.1462 | 0 | 0 | 0 | 0 | 0 | 0 | 1.3529 | 14.14 | 0 | 0 | 0 | 0 | 0 | 0.0131 | 5.5066 | 1.1227 | 4.1167 | 5.4137 | 5.103 | 5.849 | 3.2122 | 69.965 | 45.1768 | 0 | 7.8319 | 4.2298 | 7.0768 | 730.363 | 0 | 70 | 2.196 | 4.9417 | 0 | 47.4598 | 1.5562 | 4.5822 | 1.2508 | 4.961 | 2.4066 | 4.0078 | 354.075 | 210.022 | 213.75 | 205.305 | 219.92 | 204.338 | 201.793 | 201.113 | 5.0992 | 35.8566 | 49.2847 | 9.9342 | 2.0964 | 0.4996 | 1.1828 | 0.4918 | 0.761 | 0.4954 | 1.0182 | 0.3378 | 0.9109 | 0 | 154.868 | 0 | 0 | 3.4174 | 4.1171 | 7.2255 | 2.8428 | 15.7186 | 4.3225 | 0 | 2.0211 | 755.794 | 24.2959 | 0 | 0 | 0 | 0 | 0 | 0 | 1.7163 | 68.5174 | 6.4041 | 1.0611 | 10.569 | 4.5481 | 114.034 | 27.8472 | 31.2499 | 2.8657 | 36.4566 | 13.3252 | 0 | 2.4799 | 136.263 | 77.0063 | 0 | 282.522 | 364.67 | 574.011 | 128.732 | 644.36 | 112.941 | 135.817 | 91.2015 | 1 | 77.5737 | 2.3438 | 0 | 2.122 | 0.1019 | 5.9014 | 24.7224 | 14.0568 | 0 | 0 | 100 | 645.206 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 201.252 | 117.874 | 858.537 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9.838 | 0 | 1.9221 | 0 | 18.7392 | 0.4448 | 3.5701 | 6.8054 | 2.5231 | 6.047 | 0 | 0 | 4.607 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.8575 | 4.828 | 2.1221 | 9.0242 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 1.1869 | 411.426 | 73.26 | 1.0486 | 2875 | 23.42 | 1.63 | 0.3747 | 10.5828 | 0.6168 | 88.3507 | 5.6924 | 2.2249 | 1.5024 | 0.3638 | 0.934 | 0.1162 | 24.2141 | 264.156 | 0.7555 | 10.29 | 0.0489 | 4.1759 | 0.023 | 3.8954 | 6.4671 | 0.9541 | 533.914 | 2.4527 | 9.27 | 0.4407 | 3.3384 | 0.1273 | 1.7362 | 17.9666 | 0.0095 | 0.0184 | 4.6613 | 0.0062 | 192.298 | 0.4996 | 0.0326 | 0.0065 | 6.5274 | 0.0095 | 0.0184 | 0.0062 | 192.298 | 11.5591 | 103.423 | 357.582 | 9.7739 | 126.427 | 13.7328 | 28.4409 | 39.2802 | 716.514 | 0.8086 | 147.464 | 1 | 0.1206 | 631.474 | 93.5638 | 162.008 | 469.465 | 0 | -0.0416 | -0.0246 | 0.0089 | -0.0623 | 0.0083 | 1.4993 | -0.0956 | -0.0416 | -0.0264 | 6.3328 | 0.1323 | 0 | 2.3382 | 0.9905 | 1805.29 | 0.1536 | -0.0091 | 8887.52 | -0.0104 | -0.0014 | 0.0006 | 0 | 0.0001 | -0.0076 | 0 | 0.0188 | 0.0381 |
| -1 | 3009.65 | 2515.97 | -0.0072 | 0.0001 | -0.0003 | -0.0306 | -0.0093 | -0.0004 | -0.0016 | 0.0025 | -0.0851 | -0.07 | 0 | 0.9559 | 0 | 0 | 0.4628 | 0.9404 | 0 | 718.428 | 0.9907 | 58.0339 | 0.6019 | 0.9686 | 200.482 | 6.2891 | 15.92 | 4.92 | 15.96 | 15.96 | 1.399 | 2.471 | 0.7857 | 3.062 | -0.0946 | 0 | 0.7436 | 0.9971 | 2.3063 | 1006.08 | 39.14 | 131 | 74.9 | 86.3 | 53.3 | 180.863 | 7.5901 | 0.2243 | 0 | 3.78 | 0.0043 | 0.0911 | 0.036 | 0.0377 | 0.0205 | 9.1675 | 0 | 404.348 | 3.734 | 7.64 | 0.4232 | 0.0105 | 8.8051 | 0.26 | 0.0307 | 0 | 0 | 197 | 10.6751 | 2059 | 537 | 13723 | 0.151 | 0.184 | 0.149 | 2.2 | 1 | 0.149 | 0.311 | 0.9754 | 0.6475 | 0.072 | 0.2169 | 0.5249 | 0.2169 | 0.7847 | 0.2436 | 0.184 | 0 | 0 | 189.807 | 16.89 | 0.602 | 12.76 | 38.995 | 0.1701 | 7.7 | 0 | 23.88 | 38.844 | 0 | 12.5351 | 0 | 0 | 0 | 0 | 0 | 0.224 | 7.61 | 22.97 | 0.884 | 10.39 | 2216.48 | 1.4185 | 26.18 | 7.61 | 11.358 | 31.265 | 0.3344 | 7.94 | 0 | 26.18 | 106.08 | 0 | -5320.5 | 0.0617 | 0.0647 | 0.0416 | 0.0756 | 0.045 | 0.0952 | 0.069 | 0.0465 | 3.5969 | 0.0029 | 2775.25 | 0 | 0.0758 | 0.0026 | 93.6949 | 0.1323 | 1411.4 | 0 | 0.0264 | 0.0206 | 0 | -3819 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0065 | 0.0034 | 304 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.031 | 0.0193 | 0 | 1.3165 | 142.732 | 0.0007 | 1.9651 | 0.0297 | 0.0202 | 0.4234 | 0 | 0 | 0 | 0 | 2.0238 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0343 | 31.216 | 4.5258 | 7.3545 | 31.9114 | 22.5536 | 31.8371 | 19.1529 | 66.5739 | 0.0786 | 0 | 1.2819 | 0.0011 | 0.0257 | 66.9333 | 0.0114 | 0.0116 | 0.0068 | 3.2973 | 0 | 1.4344 | 2.5363 | 0.119 | 0.0034 | 3.2312 | 2.2 | 0.0787 | 0.0098 | 0 | 0 | 86.7967 | 853.891 | 248.452 | 5735.07 | 0.0726 | 0.0754 | 1242.23 | 0.1873 | 0.0664 | 0.6481 | 0.3536 | 0.0581 | 0.0915 | 0.261 | 0.0274 | 0.0901 | 0.2068 | 0.0901 | 3.3962 | 0.3216 | 0.1076 | 0.0825 | 0 | 0 | 0 | 5.6554 | 0.1879 | 3.4807 | 11.4274 | 84.7226 | 0.0462 | 1.9762 | 0 | 7.1874 | 14.2163 | 0 | 0 | 0 | 0 | 0 | 8.9635 | 0 | 0.0775 | 2.1851 | 6.4518 | 0.2496 | 3.0849 | 10.5465 | 2.1851 | 3.4577 | 9.5925 | 50.5609 | 0.1069 | 2.9031 | 0 | 7.5904 | 31.4582 | 0 | 0 | 0 | 0.0179 | 0.0328 | 64.2798 | 0.0202 | 0.0331 | 0.0128 | 0.0512 | 0.0285 | 0.0217 | 1.3744 | 0.0008 | 0 | 0.0241 | 49.4391 | 0.0008 | 30.2974 | 0.0393 | 399.007 | 0 | 0.0072 | 0.0055 | 0.0068 | 0.005 | 0 | 66.2774 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0021 | 0.0012 | 0 | 0 | 86.9622 | 0 | 0 | 0 | 0 | 0 | 0.0081 | 0.0065 | 0 | 42.7497 | 0.0002 | 118.589 | 0.6908 | 0.0103 | 0.0069 | 0.1453 | 0 | 0 | 0 | 0 | 0 | 0 | 0.8379 | 77.84 | 0 | 0 | 0 | 0 | 0 | 0.0112 | 10.5767 | 1.3543 | 6.0079 | 2.4887 | 3.243 | 3.4301 | 2.4047 | 14.5595 | 26.7732 | 0 | 3.5962 | 3.4864 | 5.6951 | 377.705 | 523.611 | 70 | 2.1483 | 4.5727 | 0 | 49.1957 | 1.8895 | 3.9648 | 1.0777 | 4.639 | 2.0742 | 2.1663 | 361.716 | 3.7027 | 74.1915 | 14.0613 | 0 | 11.4698 | 9.092 | 2.026 | 3.2869 | 45.4545 | 79.5374 | 9.8952 | 9.1572 | 0.7643 | 0.8028 | 0.429 | 0.8166 | 0.4387 | 1.184 | 0.2801 | 0.1552 | 0 | 140.445 | 0 | 0 | 4.6694 | 6.0838 | 9.0854 | 5.2273 | 13.2064 | 5.5123 | 0 | 3.7205 | 745.99 | 19.5843 | 0 | 0 | 0 | 0 | 0 | 0 | 4.9408 | 188.239 | 6.3993 | 1.2882 | 8.6948 | 8.3462 | 211.315 | 47.6899 | 48.8959 | 4.3258 | 32.0428 | 5.4374 | 0 | 4.1591 | 139.688 | 193.1 | 0 | 347.728 | 164.317 | 194.393 | 82.5553 | 659.945 | 81.0558 | 102.412 | 211.604 | 1 | 47.2323 | 2.0858 | 0 | 3.1529 | 0.2581 | 5.4186 | 65.082 | 15.1401 | 0 | 0 | 100 | 641.848 | 826.065 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 198.343 | 69.7051 | 971.429 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6.6988 | 0 | 2.05 | 0 | 19.8673 | 0.0696 | 3.3861 | 4.9428 | 2.0865 | 6.7317 | 0 | 0 | 4.659 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.4871 | 4.911 | 3.1027 | 11.5631 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 1.5941 | 406.118 | 82.076 | 1.0192 | 2848 | 17.24 | 1.57 | 0.505 | 8.2458 | 0.7845 | 63.9363 | 4.2451 | 1.9129 | 0.9799 | 0.4397 | 0.928 | 0.0728 | 44.8745 | 265.996 | 0.8106 | 4.55 | 0.099 | 1.8045 | 0.0373 | 1.7105 | 12.2083 | 0.9487 | 534.336 | 2.2662 | 9.03 | 0.2605 | 3.3888 | 0.0777 | 1.69 | 11.4947 | 0 | 0 | 4.5337 | 0 | 0 | 0.5029 | 0.0198 | 0.0042 | 3.9426 | 0.0142 | 0.0102 | 0.0031 | 71.778 | 4.0427 | 105.111 | 358.946 | 10.167 | 124.487 | 12.3891 | 15.9573 | 23.229 | 722.761 | 1.0437 | 146.025 | 1 | 0.1233 | 629.459 | 54.9354 | 0 | 0 | 0 | -0.0177 | -0.0394 | -0.0214 | -0.0916 | 0.0068 | 1.5996 | -0.1174 | -0.0674 | -0.022 | 7.6154 | 0.139 | 0 | 2.4035 | 0.9882 | 1729.14 | 0.2034 | -0.0095 | 9322.25 | -0.0376 | 0.0017 | -0.0025 | -0.0002 | 0.0001 | 0.2737 | 0 | -0.6012 | 0.026 |
| -1 | 3034.9 | 2598.02 | 0.0117 | -0.0004 | 0 | -0.0085 | -0.0126 | -0.0008 | -0.0011 | -0.0014 | -0.0618 | -0.0864 | 0 | 0.9569 | 0 | 0 | 0.4619 | 0.9626 | 0 | 724.863 | 0.9906 | 58.1685 | 0.6024 | 0.9658 | 200.272 | 6.3599 | 15.84 | 4.809 | 15.9 | 15.9 | 1.163 | 2.708 | 0.7242 | 3.025 | -0.1419 | 0 | 0.6764 | 0.9964 | 2.3044 | 997.806 | 36.287 | 136 | 213 | 169.8 | 62.7 | 610.354 | 8.7724 | 0.1262 | 0 | 7.84 | 0.0033 | 0.1156 | 0.1007 | 0.0498 | 0.0189 | 8.0723 | 0 | 401.442 | 7.712 | 6.544 | 0.3288 | 0.0134 | 7.8232 | 0.19 | 0.1041 | 0 | 0 | 1948 | 10.3867 | 644 | 508 | 95 | 0.15 | 0.096 | 0.311 | 2.2 | 0.8 | 0.099 | 0.126 | 0.9656 | 0.5844 | 0.0617 | 0.3105 | 0.5844 | 0.3105 | 0.7618 | 0.2439 | 0.192 | 0 | 0 | 189.886 | 20.53 | 0.651 | 11.62 | 36.056 | 0.1019 | 11.75 | 0 | 21.54 | 33.414 | 0 | 12.5455 | 0 | 0 | 0 | 0 | 0 | 0.252 | 3.84 | 13.69 | 0.608 | 11.81 | 2208.23 | 1.408 | 22.91 | 3.84 | 4.525 | 37.391 | 0.5246 | 12.12 | 0 | 28.86 | 91.719 | 0 | -6736 | 0.0591 | 0.186 | 0.0622 | 0.0679 | 0.0691 | 0.058 | 0.0846 | 0.0479 | 3.8882 | 0.0026 | 3136 | 0 | 0.0815 | 0.0021 | 60.2979 | 0.0328 | 618.7 | 0 | 0.0124 | 0.0139 | 0 | -4588.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.004 | 0.0037 | 1504.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0195 | 0.0157 | 0 | 0.973 | 66.8856 | 0.0007 | 2.6951 | 0.0218 | 0.0261 | 0.4527 | 0 | 0 | 0 | 0 | 1.8895 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0384 | 31.204 | 5.1375 | 5.063 | 33.7732 | 67.5417 | 52.9631 | 21.145 | 191.679 | 0.0405 | 0 | 2.3057 | 0.001 | 0.0334 | 68.2222 | 0.0259 | 0.0164 | 0.0065 | 3.0768 | 0 | 2.2919 | 1.8814 | 0.0965 | 0.0046 | 3.0483 | 1.9444 | 0.0483 | 0.037 | 0 | 0 | 905.925 | 286.895 | 245.298 | 41.9792 | 0.0666 | 0.0401 | 1517.02 | 0.155 | 0.137 | 0.7138 | 0.3005 | 0.0333 | 0.0458 | 0.2303 | 0.0313 | 0.122 | 0.2497 | 0.122 | 4.6251 | 0.2973 | 0.1059 | 0.0821 | 0 | 0 | 0 | 6.1628 | 0.1777 | 3.3214 | 11.111 | 83.6359 | 0.0257 | 3.2645 | 0 | 6.7296 | 11.0053 | 0 | 0 | 0 | 0 | 0 | 9.7836 | 0 | 0.0806 | 1.0858 | 4.7923 | 0.1615 | 3.4123 | 9.5024 | 1.0858 | 1.4986 | 11.5082 | 50.2716 | 0.1565 | 3.2246 | 0 | 8.8379 | 26.9582 | 0 | 0 | 0 | 0.0176 | 0.0788 | 64.1163 | 0.031 | 0.0319 | 0.0182 | 0.0259 | 0.0407 | 0.0212 | 1.2684 | 0.0008 | 0 | 0.0243 | 49.7284 | 0.0006 | 16.8534 | 0.0091 | 182.338 | 0 | 0.004 | 0.0044 | 0.0027 | 0.0021 | 0 | 66.5667 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0013 | 0.0012 | 0 | 0 | 87.2 | 0 | 0 | 0 | 0 | 0 | 0.0067 | 0.0047 | 0 | 20.539 | 0.0003 | 117.925 | 0.8345 | 0.0072 | 0.0094 | 0.1691 | 0 | 0 | 0 | 0 | 0 | 0 | 1.098 | 66.12 | 0 | 0 | 0 | 0 | 0 | 0.0119 | 10.9722 | 1.4918 | 6.2229 | 7.0184 | 3.242 | 6.5357 | 2.8394 | 40.2339 | 11.4929 | 0 | 7.115 | 2.6468 | 8.1873 | 0 | 424.96 | 70 | 1.978 | 4.0307 | 0 | 87.9124 | 1.6301 | 3.166 | 1.3827 | 4.12 | 1.5145 | 7.3965 | 359.586 | 28.9192 | 20.5357 | 11.0706 | 6.3133 | 15.4162 | 5.0807 | 6.1426 | 3.2248 | 41.1429 | 63.871 | 10.0026 | 2.7243 | 0.6987 | 0.6306 | 0.6176 | 0.9115 | 0.6244 | 1.1444 | 0.2797 | 0.1628 | 0 | 144.142 | 0 | 0 | 5.7093 | 6.5083 | 8.0615 | 4.8137 | 11.2794 | 8.5086 | 0 | 3.3561 | 749.027 | 26.4506 | 0 | 0 | 0 | 0 | 0 | 0 | 5.6016 | 667.3 | 3.8056 | 0.9032 | 5.9157 | 9.4694 | 210.384 | 19.7688 | 18.0869 | 5.1644 | 51.0861 | 8.1897 | 0 | 4.5633 | 138.095 | 145.789 | 0 | 0 | 397.861 | 208.9 | 66.2277 | 0 | 79.2891 | 0 | 243.456 | 1 | 56.7692 | 1.8782 | 0 | 3.4864 | 0.2071 | 3.2231 | 16.8567 | 7.2776 | 0 | 0 | 100 | 641.824 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 126.326 | 31.8408 | 493.333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4.2207 | 0 | 1.6305 | 0 | 9.2273 | 0.073 | 4.6332 | 3.6179 | 2.7075 | 7.1179 | 0 | 0 | 4.643 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.6684 | 4.857 | 3.1273 | 14.158 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 1.6361 | 409.728 | 82.684 | 3.2976 | 2852 | 23.08 | 1 | 1.3765 | 10.2235 | 0.3837 | 201.547 | 5.633 | 1.2094 | 1.0061 | 0.5058 | 0.9236 | 0.0834 | 50.2702 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.9558 | 535.524 | 2.0048 | 8.58 | 0.3274 | 3.0626 | 0.1117 | 1.6022 | 16.3329 | 0 | 0 | 4.4987 | 0 | 0 | 0.5052 | 0.0168 | 0.0044 | 3.3338 | 0.0279 | 0.0217 | 0.0061 | 77.7519 | 0.5755 | 110.19 | 359.734 | 10.2777 | 124.717 | 10.8896 | 19.4245 | 25.0179 | 724.009 | 1.0268 | 147.99 | 1 | 0.1247 | 632.441 | 62.9122 | 0 | 0 | 0 | -0.0034 | -0.0467 | -0.0298 | -0.1025 | 0.0031 | 1.4119 | -0.0732 | -0.0051 | -0.0197 | 6.8492 | 0.1384 | 0 | 2.3369 | 0.9911 | 1870.8 | 0.1944 | -0.0031 | 8501.46 | -0.0183 | 0.0011 | 0.0014 | -0.0001 | 0 | 0.1281 | 0 | -0.0068 | 0.0558 |
| -1 | 2923.19 | 2516.4 | -0.0137 | -0.0004 | 0.0001 | -0.0548 | -0.0129 | -0.0008 | 0.0008 | -0.0008 | 0.0287 | -0.0273 | 0 | 0.9613 | 0 | 0 | 0 | 0.9508 | 0 | 769.587 | 0.989 | 60.1119 | 0.602 | 0.9796 | 200.346 | 6.4207 | 15.7 | 4.04 | 15.73 | 15.71 | 1.276 | 2.533 | 0.6481 | 3.061 | 0 | 0 | 0.7048 | 0.9975 | 2.2959 | 993.899 | 36.9265 | 139 | 128.6 | 85.9 | 57.3999 | 1025.21 | 8.1512 | 0.1294 | 0 | 9.56 | 0.0035 | 0.2357 | 0.0668 | 0.0578 | 0.021 | 8.2689 | 0 | 406.454 | 5.01 | 11.211 | 0.4415 | 0.0154 | 8.1848 | 0.25 | 0.0377 | 0.0451 | 795.8 | 1148 | 9.9524 | 694 | 2869 | 2994 | 0.124 | 0.155 | 0.198 | 2.4 | 1.6 | 0.169 | 0.623 | 0.9682 | 0.5703 | 0.1315 | 0.2873 | 0.648 | 0.2873 | 0.6557 | 0.3152 | 0.415 | 0 | 0 | 190.394 | 20.59 | 0.78 | 14.54 | 16.164 | 0.1924 | 6.6 | 0 | 12.37 | 54.645 | 0 | 12.5263 | 0 | 0 | 0 | 0 | 0 | 0.147 | 8.66 | 25.86 | 0.691 | 6.24 | 2180.89 | 1.4106 | 13.93 | 8.66 | 11.87 | 19.723 | 0.143 | 9.63 | 0 | 13.93 | 86.192 | 0 | -5329.75 | 0.0822 | 0.0346 | 0.028 | 0.0651 | 0.0837 | 0.0849 | 0.1007 | 0.0694 | 2.8399 | 0.0029 | 2643.25 | 0 | 0.0909 | 0.0009 | 80.9996 | 0.0407 | 737.1 | 0 | 0.0142 | 0.016 | 0 | -4291.25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0048 | 0.0023 | -1476 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0136 | 0 | 1.331 | 97.1132 | 0.0012 | 2.6592 | 0.0336 | 0.0042 | 0.3313 | 0 | 0 | 0 | 0 | 1.9892 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0546 | 21.988 | 4.1203 | 7.4025 | 32.7834 | 39.8996 | 29.991 | 22.0624 | 332.528 | 0.043 | 0 | 3.1997 | 0.0009 | 0.0926 | 67.4889 | 0.0183 | 0.0128 | 0.0068 | 2.8865 | 0 | 1.5759 | 4.3737 | 0.1306 | 0.0049 | 2.8069 | 2.8 | 0.0734 | 0.0158 | 0.0147 | 220.941 | 499.509 | 295.213 | 1249 | 1414.68 | 0.0558 | 0.0776 | 1084.72 | 0.2313 | 0.0862 | 0.7457 | 0.5244 | 0.0642 | 0.2324 | 0.2109 | 0.0478 | 0.1269 | 0.2406 | 0.1269 | 3.4184 | 0.2723 | 0.1243 | 0.1686 | 0 | 0 | 0 | 6.9544 | 0.2477 | 4.2834 | 4.2745 | 83.9887 | 0.0499 | 2.1109 | 0 | 3.3871 | 15.4483 | 0 | 0 | 0 | 0 | 0 | 8.6968 | 0 | 0.036 | 2.4821 | 8.0226 | 0.2182 | 2.0487 | 9.4734 | 2.4821 | 3.311 | 5.8951 | 50.7955 | 0.0384 | 3.1167 | 0 | 4.3365 | 26.0127 | 0 | 0 | 0 | 0.027 | 0.0144 | 64.296 | 0.0132 | 0.0286 | 0.0241 | 0.0432 | 0.0504 | 0.0346 | 1.1803 | 0.001 | 0 | 0.0279 | 49.2045 | 0.0003 | 27.9781 | 0.0118 | 197.208 | 0 | 0.0042 | 0.0045 | 0.0032 | 0.0029 | 0 | 66.2815 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0015 | 0.0008 | 0 | 0 | 86.4285 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0041 | 0 | 27.0023 | 0.0004 | 118.197 | 0.8097 | 0.0103 | 0.0013 | 0.1064 | 0 | 0 | 0 | 0 | 0 | 0 | 0.9085 | 81.92 | 0 | 0 | 0 | 0 | 0 | 0.0208 | 7.9886 | 1.4213 | 6.4202 | 4.3993 | 2.537 | 3.4136 | 2.6319 | 94.5137 | 14.2425 | 0 | 10.1436 | 2.8551 | 17.9415 | 193.378 | 422.476 | 70 | 2.181 | 4.1273 | 0 | 61.4635 | 2.7582 | 4.4363 | 1.5946 | 4.2989 | 1.9958 | 2.672 | 365.394 | 21.5395 | 26.2556 | 66.857 | 202.845 | 9.3163 | 7.7919 | 2.6748 | 3.5561 | 57.1429 | 73.0548 | 9.9848 | 18.2247 | 0.679 | 1.5116 | 0.5656 | 1.0078 | 0.5839 | 0.9893 | 0.3647 | 0.3511 | 0 | 139.16 | 0 | 0 | 5.635 | 7.8119 | 10.4484 | 2.1638 | 14.7156 | 4.7069 | 0 | 1.9185 | 747.029 | 28.6895 | 0 | 0 | 0 | 0 | 0 | 0 | 3.2185 | 0 | 7.1057 | 1.3076 | 6.5863 | 5.2264 | 102.777 | 43.8118 | 43.0346 | 2.7414 | 14.9065 | 6.5115 | 0 | 2.2068 | 140.22 | 85.4983 | 0 | 539.016 | 181.389 | 272.506 | 0 | 769.655 | 516.109 | 368.865 | 282.688 | 1 | 36.0472 | 2.0032 | 0 | 3.8012 | 0.091 | 4.5963 | 24.8915 | 7.6895 | 0 | 0 | 100 | 644.774 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 190.47 | 37.2816 | 270.588 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.4291 | 0 | 12.6189 | 0.1226 | 4.4237 | 5.5865 | 0.4257 | 5.1603 | 0 | 0 | 4.566 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.3796 | 4.812 | 2.2123 | 11.1581 | 0.118 | 0.0118 | 0.003 | 10.0018 | 0.8189 | 407.198 | 83.108 | 0.4479 | 2888 | 18.87 | 1.19 | 0.1818 | 9.084 | 0.4836 | 54.7021 | 4.6341 | 1.4319 | 0.9485 | 0.3823 | 0.9187 | 0.0858 | 40.3018 | 264.272 | 0.5671 | 4.98 | 0.0877 | 2.0902 | 0.0382 | 1.8844 | 15.4662 | 0.9487 | 536.448 | 1.4106 | 7.05 | 0.1166 | 2.5361 | 0.0358 | 1.3142 | 8.2645 | 0 | 0 | 4.5674 | 0 | 0 | 0.4939 | 0.0163 | 0.0037 | 3.2914 | 0.0166 | 0.0122 | 0.0036 | 73.6335 | 0.2336 | 94.2467 | 363.934 | 10.4915 | 119.394 | 13.5536 | 19.7664 | 27.5825 | 719.447 | 0.9593 | 147.893 | 1 | 0.1226 | 631.22 | 100.811 | 0 | 0 | 0 | -0.0153 | -0.0191 | -0.0103 | -0.0052 | 0.0109 | 1.3137 | -0.0164 | -0.0273 | 0.0245 | 7.8782 | 0.1448 | 0 | 2.3907 | 0.9902 | 1762.29 | 0.1633 | 0.0345 | 9585.77 | 0.0911 | -0.0008 | 0.0009 | 0 | 0.0001 | -0.0367 | 0 | 0.3206 | 0.0632 |
| -1 | 2927.71 | 2525.39 | -0.0095 | 0.0004 | 0.0001 | -0.0969 | -0.0084 | -0.0005 | -0.0007 | 0.001 | 0.0356 | -0.105 | 0.9814 | 0.9761 | 101.671 | 230.036 | 0 | 0.9613 | 0 | 759.028 | 0.9656 | 56.8895 | 0.6011 | 0.9595 | 199.686 | 6.6045 | 16.07 | 4.684 | 16.09 | 16.09 | 1.757 | 2.734 | 0.7673 | 3.085 | -1.83 | 0 | 0.7182 | 0.9986 | 2.1995 | 1013.14 | 45.0112 | 87 | 76.9 | 82.4 | 46.5 | 324.855 | 5.2695 | 0.0938 | 0 | 5.07 | 0.0036 | 0.1482 | 0.0924 | 0.0486 | 0.0083 | 10.8477 | 0 | 414.113 | 4.859 | 17.502 | 0.5571 | 0.0065 | 10.3108 | 0.24 | 0.0687 | 0 | 0 | 811 | 9.9273 | 441 | 4189 | 35503 | 0.123 | 0.189 | 0.152 | 2.5 | 1.1 | 0.077 | 0.335 | 0.9798 | 0.6177 | 0.1267 | 0.3698 | 0.6515 | 0.3698 | 0.5388 | 0.2556 | 0.279 | 0 | 0 | 189.759 | 17.15 | 0.47 | 9.76 | 21.534 | 0.0614 | 6.26 | 0 | 16.06 | 23 | 0 | 12.5808 | 0 | 0 | 0 | 0 | 0 | 0.239 | 7.23 | 20.91 | 0.467 | 6.94 | 2199.66 | 1.4043 | 15.04 | 7.23 | 10.484 | 26.5081 | 0.1096 | 6.76 | 0 | 20.24 | 83.873 | 0 | -5612.25 | 0.0632 | 0.0261 | 0.0232 | 0.0241 | 0.0523 | 0.109 | 0.0778 | 0.1641 | 2.819 | 0.004 | 2636.25 | 0 | 0.051 | 0.004 | 140.573 | 0.04 | 1098.2 | 0 | 0.017 | 0.0148 | 0 | -5387.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0043 | 0.0033 | -1712.67 | 0 | 0 | 0 | 0 | 0.0007 | 0.6661 | 3.4083 | 0 | 0.0118 | 0 | 1.3173 | 101.283 | 0.0029 | 1.9951 | 0.0261 | 0.0218 | 0.3413 | 0 | 0 | 0 | 0 | 2.0033 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0206 | 26.658 | 3.4019 | 7.3308 | 22.4404 | 26.4376 | 26.9185 | 18.2407 | 92.6308 | 0.0275 | 0 | 1.8392 | 0.001 | 0.0461 | 74.0889 | 0.0286 | 0.0133 | 0.0027 | 3.3121 | 0 | 1.6664 | 5.8089 | 0.1594 | 0.0021 | 3.1605 | 2.1333 | 0.0618 | 0.0247 | 0 | 0 | 374.487 | 219.126 | 1828.03 | 17756.6 | 0.0625 | 0.08 | 1140.4 | 0.1559 | 0.0636 | 0.9649 | 0.3536 | 0.0252 | 0.1171 | 0.2497 | 0.0503 | 0.1645 | 0.2307 | 0.1645 | 3.4672 | 0.2157 | 0.1016 | 0.1176 | 0 | 0 | 0 | 5.2453 | 0.1494 | 2.7608 | 6.8882 | 85.3996 | 0.0193 | 2.0713 | 0 | 4.9341 | 7.3938 | 0 | 0 | 0 | 0 | 0 | 8.2345 | 0 | 0.085 | 2.0771 | 5.7489 | 0.1463 | 2.0437 | 8.0517 | 2.0771 | 2.8356 | 8.9255 | 50.4069 | 0.0351 | 1.8051 | 0 | 6.3431 | 25.6027 | 4.5498 | 2.8402 | 0 | 0.0204 | 0.012 | 64.3522 | 0.0096 | 0.0123 | 0.0122 | 0.0498 | 0.042 | 0.0871 | 0.9691 | 0.0012 | 0 | 0.0158 | 49.5931 | 0.0012 | 57.9374 | 0.0133 | 390.138 | 0 | 0.0041 | 0.0052 | 0.0039 | 0.003 | 0 | 66.2545 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0013 | 0.0012 | 0 | 0 | 86.6958 | 0 | 0 | 0.0002 | 0.19 | 0.9228 | 0 | 0.004 | 0 | 35.3127 | 0.0008 | 118.235 | 0.631 | 0.0101 | 0.0069 | 0.106 | 0 | 0 | 0 | 0 | 0 | 0 | 1.3369 | 79.7 | 0 | 0 | 0 | 0 | 0 | 0.0062 | 10.3794 | 1.2292 | 4.0089 | 2.6266 | 2.272 | 3.2629 | 2.114 | 28.4861 | 7.0193 | 0 | 4.9177 | 2.9352 | 10.5467 | 590.18 | 513.606 | 70 | 0.8533 | 5.4324 | 0 | 92.2091 | 4.2264 | 5.6115 | 0.6672 | 5.4336 | 1.9077 | 4.8913 | 355.888 | 14.4505 | 16.7283 | 77.7541 | 0 | 9.3376 | 9.4347 | 2.0735 | 3.3743 | 51.5625 | 49.3942 | 9.9713 | 9.6619 | 0.7233 | 1.5391 | 0.7336 | 1.0124 | 0.7457 | 0.8132 | 0.2948 | 0.236 | 0 | 139.984 | 0 | 0 | 4.8189 | 4.7135 | 6.9723 | 2.9203 | 6.7576 | 4.6518 | 0 | 2.5474 | 737.382 | 19.8632 | 0 | 0 | 0 | 0 | 0 | 0 | 5.3497 | 602.957 | 5.8469 | 0.9092 | 4.5559 | 5.7269 | 193.498 | 38.4556 | 44.0113 | 3.7149 | 12.4447 | 4.6582 | 0 | 3.244 | 134.571 | 83.0846 | 0 | 516.973 | 50.024 | 129.79 | 0 | 223.504 | 0 | 0 | 0 | 1 | 37.9556 | 3.03 | 0 | 2.0938 | 0.4123 | 7.5258 | 22.2938 | 12.7463 | 0 | 0 | 100 | 630.443 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 115.792 | 51.0386 | 643.902 | 0 | 0 | 0 | 0 | 0.0762 | 0.6551 | 1.4817 | 0 | 0 | 1.2234 | 0 | 13.3437 | 0.304 | 3.5069 | 4.35 | 2.2744 | 5.1679 | 0 | 0 | 4.612 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.9362 | 4.863 | 2.6312 | 7.5579 | 0.1094 | 0.0115 | 0.0028 | 10.4998 | 0.9713 | 404.002 | 73.192 | 0.6409 | 2852 | 15.82 | 1.52 | 0.2661 | 7.2296 | 0.5977 | 65.9908 | 3.9158 | 2.0767 | 0.9586 | 0.0821 | 0.9278 | 0.0202 | 8.57 | 256.512 | 0.7199 | 8.55 | 0.1995 | 3.6591 | 0.0992 | 3.3332 | 27.7162 | 0.9484 | 531.345 | 2.0359 | 5.71 | 0.2796 | 1.565 | 0.0936 | 1.0746 | 13.7332 | 0 | 0 | 4.4676 | 0 | 0 | 0.5055 | 0.0195 | 0.0048 | 3.8618 | 0.0184 | 0.0148 | 0.0054 | 80.1759 | 1.1991 | 103.097 | 357.623 | 10.2505 | 121.183 | 7.7727 | 18.8009 | 23.8213 | 713.561 | 0.8811 | 145.122 | 1 | 0.1227 | 623.927 | 100.949 | 156.291 | 467.636 | 0 | -0.0122 | -0.0522 | -0.0179 | -0.0007 | -0.0234 | 1.4052 | 0.0074 | -0.0073 | 0.0035 | 7.427 | 0.132 | 0 | 2.4381 | 0.9812 | 1867.88 | 0.1792 | -0.0157 | 8615.84 | 0.0454 | 0.0007 | -0.001 | 0.0001 | 0.0001 | -0.2361 | 0 | 0.2402 | 0.0381 |
| 1 | 2993.59 | 2345.95 | 0.0067 | -0.0004 | 0.0001 | 0.2263 | -0.0091 | -0.0005 | -0.0036 | -0.0018 | -0.1383 | -0.1909 | 0 | 0.9606 | 0 | 0 | 0.4573 | 0.9453 | 0 | 759.872 | 0.9909 | 58.0644 | 0.603 | 0.9658 | 199.322 | 6.2187 | 15.98 | 3.207 | 16.01 | 15.96 | 1.483 | 3.148 | 0.545 | 3.335 | -1.108 | 0 | 0.8142 | 0.998 | 2.3326 | 1013.52 | 43.4014 | 92 | 163.1 | 254 | 60.7 | 307.865 | 7.359 | 0.1184 | 0 | 6.06 | 0.0047 | 0.0946 | 0.0766 | 0.0596 | 0.0214 | 10.9006 | 0 | 416.814 | 4.342 | 10.931 | 0.7397 | 0.0145 | 10.2176 | 0.38 | 0.1493 | 0 | 0 | 109 | 9.7807 | 547 | 1075 | 1524 | 0.208 | 0.098 | 0.113 | 1.8 | 0.7 | 0.063 | 0.315 | 0.9695 | 0.538 | 0.1308 | 0.2099 | 0.5536 | 0.2099 | 0.8605 | 0.2363 | 0.227 | 0 | 0 | 189.541 | 17.48 | 0.61 | 7.07 | 19.308 | 0.0763 | 4.23 | 0 | 13.19 | 26.241 | 0 | 12.4622 | 0 | 0 | 0 | 0 | 0 | 0.246 | 9.5 | 18.06 | 0.28 | 4.53 | 2169.47 | 1.3733 | 21.28 | 9.5 | 14.06 | 27.685 | 0.3718 | 19.73 | 0 | 21.28 | 80.561 | 0 | -5300.25 | 0.0806 | 0.0575 | 0.0969 | 0.0208 | 0.0639 | 0.1006 | 0.1003 | 0.0963 | 3.8399 | 0.0043 | 2631 | 0 | 0.0436 | 0.0084 | 88.7012 | 0.0268 | 1572.6 | 0 | 0.0283 | 0.0356 | 0 | -3525.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0088 | 0.0041 | -485.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1918 | 0.01 | 0 | 1.289 | 130.823 | 0.0011 | 3.7145 | 0.023 | 0.026 | 0.4019 | 0 | 0 | 0 | 0 | 2.0105 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0588 | 18.48 | 2.3121 | 7.2763 | 26.3184 | 65.3567 | 85.0263 | 20.8461 | 97.8339 | 0.0333 | 0 | 2.1868 | 0.0012 | 0.03 | 69.0667 | 0.0217 | 0.0164 | 0.0072 | 3.4068 | 0 | 1.3986 | 3.0585 | 0.2253 | 0.0047 | 3.2428 | 2.2667 | 0.1232 | 0.0559 | 0 | 0 | 48.9583 | 262.827 | 504.386 | 749.711 | 0.0973 | 0.0464 | 1185.44 | 0.144 | 0.0525 | 0.5895 | 0.2449 | 0.024 | 0.1169 | 0.2099 | 0.0541 | 0.0758 | 0.2105 | 0.0758 | 3.4006 | 0.3387 | 0.0928 | 0.0877 | 0 | 0 | 0 | 4.7265 | 0.1953 | 2.1588 | 5.6056 | 101.907 | 0.0254 | 1.3072 | 0 | 3.8678 | 6.7717 | 0 | 0 | 0 | 0 | 0 | 23.3453 | 0 | 0.0769 | 2.6724 | 5.9064 | 0.098 | 1.0725 | 9.0885 | 2.6724 | 3.6487 | 7.4193 | 57.6663 | 0.1168 | 5.6218 | 0 | 5.7689 | 28.8787 | 5.5701 | 7.2559 | 0 | 0.0235 | 0.0257 | 74.7081 | 0.0408 | 0.0107 | 0.0164 | 0.0534 | 0.0437 | 0.0498 | 1.2703 | 0.0014 | 0 | 0.0142 | 42.3337 | 0.003 | 29.847 | 0.0073 | 532.783 | 0 | 0.0084 | 0.0102 | 0.0048 | 0.0036 | 0 | 66.8426 | 0 | 0 | 0 | 0 | 0 | 0 | 0.003 | 0.0017 | 0 | 0 | 86.9275 | 0 | 0 | 0 | 0 | 0 | 0.0309 | 0.0036 | 0 | 49.354 | 0.0004 | 126.566 | 1.2535 | 0.0075 | 0.0078 | 0.1371 | 0 | 0 | 0 | 0 | 0 | 0 | 1.2412 | 65.83 | 0 | 0 | 0 | 0 | 0 | 0.0179 | 5.839 | 0.8497 | 4.0737 | 5.4483 | 5.171 | 10.8272 | 2.7979 | 25.9704 | 9.5426 | 0 | 6.0093 | 3.8485 | 6.0902 | 443.897 | 884.601 | 70 | 2.2267 | 5.4689 | 0 | 59.0026 | 2.6225 | 7.5628 | 1.4986 | 5.3907 | 3.0492 | 10.8708 | 362.182 | 2.0565 | 20.7906 | 30.4921 | 313.903 | 16.1365 | 4.8744 | 1.553 | 2.6062 | 30.8824 | 43.75 | 9.9914 | 9.2632 | 0.5279 | 0.5603 | 0.364 | 0.741 | 0.4958 | 1.2874 | 0.2718 | 0.1794 | 0 | 125.326 | 0 | 0 | 4.8263 | 6.1053 | 5.6413 | 2.6706 | 8.0648 | 3.003 | 0 | 2.0991 | 722.996 | 21.1771 | 0 | 0 | 0 | 0 | 0 | 0 | 5.3095 | 37.9421 | 5.0221 | 0.9465 | 2.6712 | 4.1046 | 219.586 | 63.495 | 69.586 | 3.9393 | 36.8704 | 13.2681 | 0 | 3.4396 | 140.857 | 130.377 | 0 | 294.631 | 104.975 | 193.413 | 45.7143 | 240.621 | 133.422 | 338.28 | 257.716 | 1 | 52.8428 | 3.1587 | 0 | 1.7999 | 0.8621 | 4.8295 | 17.1238 | 17.8696 | 0 | 788.85 | 100 | 628.365 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 123.912 | 96.9697 | 745.455 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 41.9486 | 0 | 1.0566 | 0 | 17.2164 | 0.1128 | 6.3972 | 3.8073 | 2.6887 | 6.4626 | 0 | 0 | 4.549 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.5188 | 4.785 | 1.8233 | 5.3272 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 1.1443 | 401.278 | 73.89 | 0.7029 | 2908 | 20.23 | 0.67 | 0.3299 | 8.9451 | 0.28 | 61.4214 | 5.0414 | 0.9068 | 0.9754 | 0.0706 | 0.9261 | 0.0218 | 7.2369 | 261.338 | 0.7496 | 7.94 | 0.1314 | 3.3165 | 0.0508 | 3.0382 | 17.5247 | 0.9506 | 530.997 | 2.1898 | 7.23 | 0.3743 | 2.5312 | 0.1159 | 1.3616 | 17.0935 | 0.0246 | 0.0138 | 4.6332 | 0.0037 | 56.0357 | 0.4976 | 0.0087 | 0.0024 | 1.7469 | 0.0246 | 0.0138 | 0.0037 | 56.0357 | 25.0382 | 100.844 | 359.607 | 10.4823 | 110.364 | 9.691 | 14.9618 | 20.2052 | 702.791 | 1.0083 | 148.703 | 1 | 0.1221 | 618.674 | 61.7909 | 155.852 | 462.822 | 0 | -0.0274 | -0.0548 | 0.0501 | 0.0455 | 0.0266 | 1.5533 | -0.0754 | -0.0296 | -0.0374 | 7.2666 | 0.1361 | 0 | 2.4222 | 0.9707 | 1836.65 | 0.1567 | 0.0173 | 8800.4 | -0.0451 | 0.0036 | 0.0017 | 0 | -0.0001 | 0.0715 | 0 | 0.1203 | 0.0409 |
| -1 | 3048.76 | 2545.68 | 0.0031 | 0 | 0 | 0.0286 | -0.0114 | 0 | 0.0004 | -0.0015 | 0.0416 | 0.0501 | 0.9763 | 0.9679 | 101.363 | 233.342 | 0.4691 | 0.9593 | 0 | 782.551 | 0.9913 | 57.1869 | 0.5995 | 0.9693 | 199.049 | 6.223 | 15.75 | 3.235 | 15.8 | 15.73 | 0.9838 | 2.783 | 0.5653 | 3.153 | 0.7096 | 0 | 0.8543 | 0.9962 | 2.2802 | 998.012 | 37.2972 | 122 | 141.8 | 101.7 | 51.5 | 184.64 | 9.8057 | 0.33 | 0 | 5.65 | 0.0033 | 0.1041 | 0.0616 | 0.0442 | 0.0088 | 6.2609 | 0 | 407.589 | 11.998 | 4.916 | 0.2378 | 0.0053 | 6.0231 | 0.2 | 0.0294 | 0 | 0 | 453 | 10.4536 | 339 | 1237 | 21789 | 0.107 | 0.17 | 0.247 | 3 | 1.1 | 0.118 | 0.292 | 0.9809 | 0.6458 | 0.1516 | 0.3272 | 0.631 | 0.3272 | 0.8332 | 0.3278 | 0.26 | 0 | 0 | 188.596 | 14.82 | 0.413 | 4.37 | 26.363 | 0.2082 | 11.63 | 0 | 20.3 | 19.791 | 0 | 12.512 | 0 | 0 | 0 | 0 | 0 | 0.259 | 6.37 | 17.4 | 0.218 | 6.94 | 2224.68 | 1.3924 | 21.37 | 6.37 | 9.37 | 34.05 | 0.0966 | 7.04 | 0 | 21.37 | 92.365 | 0 | -5122.5 | 0.0542 | 0.0323 | 0.0334 | 0.0266 | 0.0515 | 0.0167 | 0.0702 | 0.0412 | 3.936 | 0.0038 | 2541.5 | 0.01 | 0.0748 | 0.0017 | 157.449 | 0.0305 | 493.1 | 0 | 0.0121 | 0.0163 | 0 | -3889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0035 | 0.0045 | 6309.25 | 0 | 0 | 0 | 0 | 0.0061 | 0.4214 | 3.7503 | 0.0196 | 0.0109 | 0 | 1.296 | 56.9557 | 0.0007 | 1.6717 | 0.0359 | 0.0127 | 0.1769 | 0 | 0 | 0 | 0 | 1.9937 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.044 | 31.404 | 4.1345 | 7.2325 | 31.184 | 48.7266 | 32.2895 | 19.3278 | 59.5384 | 0.1099 | 0 | 1.9283 | 0.0009 | 0.0319 | 70.9889 | 0.0187 | 0.0129 | 0.003 | 2.1308 | 0 | 3.0225 | 1.7083 | 0.0752 | 0.0017 | 2.0624 | 1.9333 | 0.0539 | 0.0106 | 0 | 0 | 203.684 | 145.599 | 510.639 | 10767.3 | 0.045 | 0.0839 | 1308.65 | 0.1668 | 0.1259 | 0.9727 | 0.3279 | 0.0399 | 0.1002 | 0.2424 | 0.062 | 0.1365 | 0.2336 | 0.1365 | 3.3848 | 0.3319 | 0.1197 | 0.0959 | 0 | 0 | 0 | 5.1057 | 0.1315 | 1.5877 | 8.1451 | 84.361 | 0.059 | 3.2962 | 0 | 6.8428 | 5.3688 | 0 | 0 | 0 | 0 | 0 | 8.8624 | 0 | 0.085 | 2.0694 | 5.8436 | 0.0764 | 2.1734 | 9.5915 | 2.0694 | 2.9555 | 10.6843 | 50.8411 | 0.0368 | 2.5103 | 0 | 6.3284 | 28.091 | 0 | 0 | 0 | 0.0154 | 0.0154 | 64.6702 | 0.0145 | 0.0125 | 0.0121 | 0.0078 | 0.0385 | 0.017 | 1.275 | 0.0011 | 0.0027 | 0.0235 | 49.1589 | 0.0006 | 51.7392 | 0.0105 | 146.777 | 0 | 0.0035 | 0.0038 | 0.0028 | 0.0033 | 0 | 66.2314 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0011 | 0.0016 | 0 | 0 | 86.3364 | 0 | 0 | 0.0021 | 0.1461 | 1.0762 | 0.0052 | 0.0038 | 0 | 17.5397 | 0.0002 | 118.309 | 0.5007 | 0.0106 | 0.0045 | 0.0642 | 0 | 0 | 0 | 0 | 0 | 0 | 1.3907 | 81.74 | 0 | 0 | 0 | 0 | 0 | 0.0131 | 11.7622 | 1.2469 | 5.5674 | 4.6511 | 2.673 | 3.995 | 2.3149 | 14.1092 | 23.7274 | 0 | 5.5867 | 2.7308 | 7.1481 | 815.894 | 0 | 70 | 0.9131 | 3.1454 | 0 | 122.357 | 1.2061 | 2.275 | 0.5418 | 3.1936 | 1.5985 | 2.1143 | 352.305 | 8.8433 | 13.3386 | 31.8077 | 345.35 | 8.2562 | 8.5266 | 3.4151 | 4.226 | 56.8966 | 70.7528 | 10.3971 | 8.6269 | 0.7655 | 1.711 | 0.6436 | 0.9757 | 0.6656 | 1.258 | 0.3797 | 0.2198 | 0 | 122.251 | 0 | 0 | 4.2066 | 3.9723 | 3.5746 | 3.7061 | 17.7149 | 8.2835 | 0 | 3.301 | 711.343 | 36.519 | 0 | 0 | 0 | 0 | 0 | 0 | 5.5872 | 129.687 | 4.9633 | 1.175 | 2.0277 | 6.4761 | 168.533 | 42.2185 | 48.5912 | 4.9201 | 9.5007 | 4.8707 | 0 | 3.5482 | 140.4 | 82.9294 | 0 | 250.781 | 50.2528 | 364.033 | 59.0783 | 239.535 | 86.4166 | 450.722 | 460.335 | 1 | 52.9028 | 2.9559 | 8.6728 | 3.0417 | 0.1708 | 8.3174 | 16.1325 | 5.4426 | 0 | 0 | 100 | 614.956 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 54.1936 | 30.837 | 0 | 0 | 0 | 0 | 0 | 0.6295 | 0.4158 | 1.6072 | 4.1715 | 0 | 1.1378 | 0 | 7.2782 | 0.0656 | 2.9233 | 5.9811 | 1.307 | 2.8428 | 0 | 0 | 4.584 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.9293 | 4.834 | 3.1467 | 11.0853 | 0.1152 | 0.01 | 0.0027 | 8.6728 | 0 | 0 | 0 | 0 | 2855 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.9978 | 0.6573 | 0.9314 | 0.1054 | 65.8707 | 264.272 | 0.5671 | 4.98 | 0.0877 | 2.0902 | 0.0382 | 1.8844 | 15.4662 | 0.9483 | 529.744 | 2.2313 | 7.19 | 0.2345 | 2.4961 | 0.0792 | 1.3573 | 10.5084 | 0 | 0 | 4.6356 | 0 | 0 | 0.5032 | 0.0129 | 0.0034 | 2.5678 | 0.0099 | 0.0113 | 0.0038 | 114.288 | 4.9118 | 101.133 | 350.576 | 10.751 | 107.163 | 12.68 | 15.0882 | 19.2834 | 692.06 | 1.0171 | 144.537 | 1 | 0.1208 | 602.276 | 111.378 | 0 | 0 | 0 | 0.0216 | -0.0643 | -0.0092 | 0.045 | -0.0215 | 1.4563 | 0.0193 | -0.0156 | 0.0089 | 7.44 | 0.1286 | 0.1152 | 2.4604 | 0.9896 | 1893.02 | 0.1893 | 0.0075 | 9060.02 | 0.0118 | -0.0004 | 0.0015 | 0 | 0 | -0.0185 | 0 | 0.0183 | -0.0028 |
| -1 | 2977.74 | 2611.5 | -0.0012 | 0.0002 | 0 | -0.0681 | -0.0118 | 0.0003 | -0.0051 | -0.0009 | -0.1163 | -0.1348 | 0.9827 | 0.9655 | 98.5044 | 234.248 | 0 | 0.9536 | 0 | 736.706 | 0.9896 | 58.2458 | 0.5934 | 0.9812 | 197.215 | 6.3603 | 15.74 | 4.635 | 15.77 | 15.75 | 1.513 | 2.832 | 0.7813 | 3.325 | -1.088 | 0 | 0.4199 | 0.9979 | 2.2785 | 1011.88 | 64.1287 | 104 | 87.4 | 121.1 | 57.7 | 644.683 | 8.9226 | 1.3101 | 0 | 5.55 | 0.0074 | 0.2361 | 0.0414 | 0.0714 | 0.0151 | 4.0358 | 0 | 399.163 | 5.747 | 4.904 | 0.1782 | 0.0098 | 3.9573 | 0.24 | 0.0471 | 0 | 0 | 856 | 10.5147 | 269 | 1544 | 1967 | 0.143 | 0.037 | 0.285 | 2.1 | 1 | 0.124 | 0.368 | 0.9747 | 1.153 | 0.1057 | 0.2214 | 0.4827 | 0.2214 | 0.944 | 0.1346 | 0.871 | 0 | 0 | 186.701 | 18.03 | 0.384 | 7.35 | 23.102 | 0.108 | 3.16 | 0 | 18.57 | 41.772 | 0 | 12.4267 | 0 | 0 | 0 | 0 | 0 | 0.231 | 4.69 | 19.55 | 0.544 | 7.09 | 2192.79 | 1.3915 | 16.08 | 4.69 | 6.747 | 24.97 | 0.12 | 6.88 | 0 | 20.14 | 47.5 | 0 | -5138.5 | 0.0755 | 0.0652 | 0.0799 | 0.0119 | 0.1016 | 0.117 | 0.0704 | 0.0738 | 3.0482 | 0.0044 | 2519.75 | 0 | 0.0333 | 0.002 | 146.793 | 0.029 | 641.9 | 0 | 0.0291 | 0.0194 | 0 | -3568.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0056 | 0.003 | -437.5 | 0 | 0 | 0 | 0 | 0.002 | 4.3542 | 5.0897 | 0 | 0.0138 | 0 | 1.3058 | 66.4055 | 0.0008 | 3.2866 | 0.0279 | 0.0029 | 0.2517 | 0 | 0 | 0 | 0 | 1.9625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0999 | 12.07 | 3.6156 | 7.2393 | 27.6624 | 26.2132 | 44.8352 | 20.4838 | 187.297 | 0.4877 | 0 | 1.835 | 0.0019 | 0.0717 | 72.7889 | 0.0131 | 0.018 | 0.005 | 1.4798 | 0 | 1.9837 | 1.6155 | 0.0623 | 0.0033 | 1.4668 | 2.3444 | 0.0658 | 0.0166 | 0 | 0 | 408.334 | 124.519 | 676.016 | 840.943 | 0.0762 | 0.0157 | 1268.59 | 0.1779 | 0.1308 | 0.69 | 0.3283 | 0.0395 | 0.1403 | 0.475 | 0.0418 | 0.087 | 0.1982 | 0.087 | 3.5174 | 0.3798 | 0.0485 | 0.3293 | 0 | 0 | 0 | 5.7323 | 0.1197 | 2.4163 | 7.1052 | 105.604 | 0.0331 | 0.9783 | 0 | 5.4133 | 13.641 | 0 | 0 | 0 | 0 | 0 | 7.6032 | 0 | 0.079 | 1.4979 | 6.0679 | 0.1918 | 2.0654 | 8.619 | 1.4979 | 1.9396 | 8.2409 | 58.8024 | 0.0353 | 1.9742 | 0 | 5.8375 | 16.552 | 0 | 0 | 0 | 0.024 | 0.0287 | 76.1632 | 0.0376 | 0.0051 | 0.03 | 0.0569 | 0.0311 | 0.0327 | 1.2328 | 0.0016 | 0 | 0.0117 | 41.1976 | 0.0006 | 44.3981 | 0.01 | 188.068 | 0 | 0.0065 | 0.0053 | 0.0042 | 0.003 | 0 | 66.396 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0019 | 0.0009 | 0 | 0 | 87.2358 | 0 | 0 | 0.0006 | 1.1665 | 1.6193 | 0 | 0.0051 | 0 | 22.1358 | 0.0002 | 126.079 | 1.1426 | 0.0091 | 0.001 | 0.0956 | 0 | 0 | 0 | 0 | 0 | 0 | 1.9935 | 80.85 | 0 | 0 | 0 | 0 | 0 | 0.0368 | 3.595 | 1.2929 | 4.8145 | 2.9351 | 4.155 | 4.6372 | 2.6314 | 50.8191 | 65.7172 | 0 | 5.3066 | 5.8358 | 16.5785 | 972.687 | 0 | 70 | 1.5606 | 2.0464 | 0 | 64.4092 | 1.2286 | 1.6947 | 1.0047 | 2.1196 | 1.9313 | 3.3826 | 356.818 | 16.6586 | 10.6757 | 43.2675 | 449.6 | 10.9516 | 1.8854 | 3.9369 | 2.8851 | 42.654 | 69.7064 | 9.7779 | 10.4621 | 1.0918 | 1.3907 | 0.3765 | 0.6338 | 0.5374 | 1.4218 | 0.1543 | 0.6908 | 0 | 149.114 | 0 | 0 | 5.053 | 3.9272 | 4.9291 | 3.0832 | 8.8808 | 2.3427 | 0 | 2.8979 | 749.279 | 18.8678 | 0 | 0 | 0 | 0 | 0 | 0 | 5.0386 | 221.701 | 5.4613 | 1.2163 | 5.4601 | 5.5828 | 169.595 | 21.2068 | 26.073 | 3.4517 | 8.8797 | 4.6677 | 0 | 3.1849 | 134.885 | 27.1926 | 0 | 0 | 0 | 206.061 | 36.6436 | 999.139 | 960.986 | 87.8353 | 118.554 | 1 | 45.3555 | 3.1047 | 0 | 1.4057 | 0.2049 | 8.2226 | 17.1801 | 7.2553 | 0 | 566.423 | 100 | 640.816 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 221.393 | 47.6089 | 960 | 0 | 0 | 0 | 0 | 0.2035 | 4.4203 | 2.1728 | 0 | 0 | 1.4478 | 0 | 9.0138 | 0.0779 | 5.6427 | 4.7004 | 0.2983 | 3.958 | 0 | 0 | 4.564 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4.3832 | 4.794 | 1.1928 | 5.638 | 0.1128 | 0.0079 | 0.0021 | 6.9742 | 0.8638 | 391.438 | 73.248 | 0.3042 | 2883 | 14.06 | 0.85 | 0.1219 | 6.3642 | 0.3433 | 35.2166 | 3.5919 | 1.1604 | 1.0519 | 0.3136 | 0.9304 | 0.0737 | 29.8161 | 264.272 | 0.5671 | 4.98 | 0.0877 | 2.0902 | 0.0382 | 1.8844 | 15.4662 | 0.952 | 534.326 | 1.5887 | 5.4 | 0.2039 | 1.8036 | 0.054 | 1.0106 | 12.833 | 0.0363 | 0.0135 | 4.5846 | 0.0044 | 37.2277 | 0.5003 | 0.0165 | 0.0037 | 3.2961 | 0.0363 | 0.0135 | 0.0044 | 37.2277 | -2.1155 | 104.587 | 357.971 | 9.9633 | 126.998 | 9.4814 | 22.1155 | 25.8775 | 723.401 | 1.3511 | 147.395 | 1 | 0.1268 | 632.365 | 174.68 | 0 | 0 | 0 | -0.0067 | 0.0012 | -0.0388 | -0.0325 | 0.0102 | 1.4241 | -0.0122 | -0.0801 | -0.0623 | 6.7207 | 0.1413 | 0 | 2.3718 | 0.9708 | 1785.25 | 0.1691 | -0.0043 | 8847.39 | 0.1654 | 0.0051 | 0.0009 | 0 | 0.0001 | -0.0274 | 0 | -0.0966 | -0.0233 |
| -1 | 3044.88 | 2636.69 | 0.0003 | -0.0002 | -0.0001 | -0.0984 | -0.0134 | 0.0008 | 0.0016 | 0.0075 | -0.1333 | -0.1378 | 0 | 0.9679 | 0 | 0 | 0.46 | 0.9437 | 0 | 744.705 | 0.9662 | 56.281 | 0.6063 | 0.9659 | 199.994 | 6.3729 | 15.74 | 3.494 | 15.75 | 15.75 | 1.078 | 2.688 | 0.536 | 2.816 | -0.0473 | 0 | 0.6887 | 0.999 | 2.3259 | 996.216 | 39.4787 | 110 | 259.8 | 193.3 | 52.3 | 263.888 | 6.0974 | 0.2879 | 0 | 7.51 | 0.0044 | 0.1217 | 0.0394 | 0.047 | 0.0169 | 7.7121 | 0 | 408.071 | 2.6 | 9.978 | 0.6743 | 0.0144 | 7.0378 | 0.85 | 0.0714 | 0 | 0 | 424 | 9.9073 | 236 | 6797 | 1302 | 0.137 | 0.138 | 0.137 | 2.4 | 0.9 | 0.248 | 0.287 | 0.9648 | 0.6531 | 0.1175 | 0.3377 | 0.6535 | 0.3376 | 0.5457 | 0.1211 | 0.964 | 0 | 0 | 190.086 | 15.42 | 0.481 | 15.79 | 40.1 | 0.2001 | 10.24 | 0 | 19.76 | 49.572 | 0 | 12.5471 | 0 | 0 | 0 | 0 | 0 | 0.29 | 5.91 | 19.8 | 0.347 | 11.56 | 2230.76 | 1.402 | 21.12 | 5.91 | 7.747 | 40.601 | 0.1284 | 9.6 | 0 | 21.12 | 42.44 | 0 | -5711 | 0.0761 | 0.0855 | 0.0245 | 0.032 | 0.0633 | 0.0378 | 0.0752 | 0.0538 | 4.072 | 0.0034 | 2627.5 | 0 | 0.0829 | 0.0116 | 144.423 | 0.0633 | 796.301 | 0 | 0.0177 | 0.0208 | 0 | -4862.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0062 | 0.005 | -1757.67 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0099 | 0.0471 | 0 | 1.2435 | 95.5123 | 0.003 | 3.0673 | 0.0285 | 0.0219 | 0.3657 | 0 | 0 | 0 | 0 | 2.0275 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.044 | 32.527 | 3.5332 | 7.255 | 29.161 | 76.5649 | 58.5933 | 16.5502 | 92.7185 | 0.0979 | 0 | 2.3562 | 0.0011 | 0.0421 | 67.2667 | 0.0141 | 0.0144 | 0.0058 | 2.8805 | 0 | 0.9404 | 3.1883 | 0.191 | 0.0046 | 2.7516 | 2.6111 | 0.1207 | 0.0259 | 0 | 0 | 186.549 | 100.058 | 2942.96 | 681.984 | 0.059 | 0.0646 | 1281.79 | 0.188 | 0.0569 | 0.7874 | 0.2759 | 0.0714 | 0.11 | 0.2525 | 0.0534 | 0.1268 | 0.2614 | 0.1268 | 3.5019 | 0.2106 | 0.0443 | 0.4006 | 0 | 0 | 0 | 5.0376 | 0.1455 | 4.2365 | 11.7333 | 83.7263 | 0.0513 | 3.1769 | 0 | 6.3454 | 16.2615 | 0 | 0 | 0 | 0 | 0 | 8.7867 | 0 | 0.0848 | 1.5715 | 5.9362 | 0.1218 | 3.141 | 9.6856 | 1.5715 | 2.7164 | 11.9693 | 50.198 | 0.0332 | 2.9055 | 0 | 6.6539 | 14.5353 | 5.5542 | 2.3102 | 0 | 0.0208 | 0.0354 | 64.0159 | 0.0106 | 0.0133 | 0.0201 | 0.0156 | 0.043 | 0.0238 | 1.1696 | 0.001 | 0 | 0.0264 | 49.802 | 0.004 | 45.1974 | 0.0195 | 216.999 | 0 | 0.0051 | 0.0065 | 0.0033 | 0.0031 | 0 | 66.3724 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0023 | 0.0017 | 0 | 0 | 86.5708 | 0 | 0 | 0 | 0 | 0 | 0.0033 | 0.015 | 0 | 26.8271 | 0.001 | 118.691 | 0.7859 | 0.0102 | 0.0069 | 0.1322 | 0 | 0 | 0 | 0 | 0 | 0 | 1.0038 | 76.15 | 0 | 0 | 0 | 0 | 0 | 0.0143 | 13.0513 | 1.2142 | 4.9878 | 8.5324 | 2.956 | 7.3312 | 2.3445 | 20.5875 | 28.6801 | 0 | 6.7325 | 3.5622 | 8.1853 | 121.207 | 0 | 70 | 1.7501 | 3.8562 | 0 | 42.6414 | 2.4452 | 6.8062 | 1.4885 | 3.7024 | 6.7745 | 5.0943 | 355.038 | 7.4243 | 8.9819 | 139.777 | 74.0755 | 11.0173 | 6.8064 | 1.8884 | 3.5679 | 34.4681 | 131.915 | 10.0061 | 8.1956 | 0.78 | 1.3368 | 0.6727 | 1.0208 | 0.6779 | 0.8222 | 0.1399 | 0.8122 | 0 | 140.285 | 0 | 0 | 4.3432 | 4.8071 | 11.2557 | 5.4253 | 14.6871 | 7.2189 | 0 | 3.1012 | 739.127 | 25.725 | 0 | 0 | 0 | 0 | 0 | 0 | 6.3869 | 574.293 | 5.5708 | 1.3626 | 3.3442 | 9.529 | 126.44 | 31.153 | 29.1922 | 5.6977 | 12.6899 | 6.679 | 0 | 3.4039 | 141.851 | 48.2702 | 0 | 0 | 122.801 | 0 | 50.3937 | 592.627 | 72.2753 | 310.423 | 262.119 | 1 | 57.6737 | 2.6526 | 0 | 3.4544 | 1.2037 | 7.7438 | 36.8026 | 9.2971 | 0 | 0 | 100 | 637.174 | 278.261 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 192.7 | 46.1825 | 625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.1441 | 0 | 4.9908 | 0 | 12.8255 | 0.3063 | 5.45 | 4.7008 | 2.2679 | 5.7385 | 0 | 0 | 4.612 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.8899 | 4.851 | 3.2651 | 8.9496 | 0.1096 | 0.0078 | 0.0026 | 7.116 | 1.5427 | 394.352 | 71.786 | 1.658 | 2847 | 15.41 | 1.02 | 0.65 | 7.2286 | 0.4317 | 107.477 | 3.9077 | 1.4209 | 0.9755 | 0.1623 | 0.9289 | 0.0397 | 16.633 | 264.272 | 0.5671 | 4.98 | 0.0877 | 2.0902 | 0.0382 | 1.8844 | 15.4662 | 0.9506 | 532.761 | 1.9518 | 7.9901 | 0.1517 | 2.8686 | 0.042 | 1.4997 | 7.7724 | 0 | 0 | 4.5406 | 0 | 0 | 0.4987 | 0.0138 | 0.0036 | 2.7637 | 0.0193 | 0.0122 | 0.004 | 63.0838 | 1.0291 | 111.549 | 355.423 | 10.376 | 121.314 | 16.7036 | 18.9709 | 26.5379 | 712.589 | 1.0115 | 143.734 | 1 | 0.1235 | 620.47 | 87.9218 | 156.171 | 464.299 | 0 | -0.0058 | -0.0696 | 0.0018 | -0.0635 | 0.0107 | 1.4868 | 0.0523 | -0.0242 | -0.0205 | 7.0604 | 0.1282 | 0 | 2.4005 | 0.9619 | 1865 | 0.172 | -0.0325 | 8565.08 | 0.1393 | -0.0015 | -0.0075 | -0.0001 | -0.0001 | 0.1928 | 0 | -0.2285 | -0.0595 |
response2 = "C1"
fm2 = df2.col_names
fm2.remove(response2)
df2.pca.train(x=fm2, training_frame=df2)
pca Model Build progress: |██████████████████████████████████████████████████████| (done) 100% Model Details ============= H2OPrincipalComponentAnalysisEstimator : Principal Components Analysis Model Key: PCA_model_python_1638771670270_13 Importance of components:
| pc1 | pc2 | pc3 | pc4 | pc5 | pc6 | pc7 | pc8 | pc9 | ... | pc61 | pc62 | pc63 | pc64 | pc65 | pc66 | pc67 | pc68 | pc69 | pc70 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Standard deviation | 14912.090624 | 6365.402970 | 4101.434915 | 2600.961311 | 1625.477034 | 1204.577424 | 1011.360523 | 963.102042 | 573.311672 | ... | 35.103439 | 34.577217 | 33.492329 | 32.860702 | 31.849359 | 30.027758 | 29.474500 | 28.783870 | 27.887428 | 25.663299 |
| 1 | Proportion of Variance | 0.752634 | 0.137138 | 0.056935 | 0.022897 | 0.008943 | 0.004911 | 0.003462 | 0.003139 | 0.001112 | ... | 0.000004 | 0.000004 | 0.000004 | 0.000004 | 0.000003 | 0.000003 | 0.000003 | 0.000003 | 0.000003 | 0.000002 |
| 2 | Cumulative Proportion | 0.752634 | 0.889772 | 0.946707 | 0.969603 | 0.978546 | 0.983457 | 0.986919 | 0.990059 | 0.991171 | ... | 0.999946 | 0.999951 | 0.999954 | 0.999958 | 0.999961 | 0.999964 | 0.999967 | 0.999970 | 0.999973 | 0.999975 |
3 rows × 71 columns
ModelMetricsPCA: pca ** Reported on train data. ** MSE: NaN RMSE: NaN Scoring History for GramSVD:
| timestamp | duration | iterations | ||
|---|---|---|---|---|
| 0 | 2021-12-06 19:13:35 | 1.029 sec | 0.0 |
df2.pca
Model Details ============= H2OPrincipalComponentAnalysisEstimator : Principal Components Analysis Model Key: PCA_model_python_1638771670270_13 Importance of components:
| pc1 | pc2 | pc3 | pc4 | pc5 | pc6 | pc7 | pc8 | pc9 | ... | pc61 | pc62 | pc63 | pc64 | pc65 | pc66 | pc67 | pc68 | pc69 | pc70 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Standard deviation | 14912.090624 | 6365.402970 | 4101.434915 | 2600.961311 | 1625.477034 | 1204.577424 | 1011.360523 | 963.102042 | 573.311672 | ... | 35.103439 | 34.577217 | 33.492329 | 32.860702 | 31.849359 | 30.027758 | 29.474500 | 28.783870 | 27.887428 | 25.663299 |
| 1 | Proportion of Variance | 0.752634 | 0.137138 | 0.056935 | 0.022897 | 0.008943 | 0.004911 | 0.003462 | 0.003139 | 0.001112 | ... | 0.000004 | 0.000004 | 0.000004 | 0.000004 | 0.000003 | 0.000003 | 0.000003 | 0.000003 | 0.000003 | 0.000002 |
| 2 | Cumulative Proportion | 0.752634 | 0.889772 | 0.946707 | 0.969603 | 0.978546 | 0.983457 | 0.986919 | 0.990059 | 0.991171 | ... | 0.999946 | 0.999951 | 0.999954 | 0.999958 | 0.999961 | 0.999964 | 0.999967 | 0.999970 | 0.999973 | 0.999975 |
3 rows × 71 columns
ModelMetricsPCA: pca ** Reported on train data. ** MSE: NaN RMSE: NaN Scoring History for GramSVD:
| timestamp | duration | iterations | ||
|---|---|---|---|---|
| 0 | 2021-12-06 19:13:35 | 1.029 sec | 0.0 |
df2.pca.varimp(use_pandas=True)
| pc1 | pc2 | pc3 | pc4 | pc5 | pc6 | pc7 | pc8 | pc9 | ... | pc61 | pc62 | pc63 | pc64 | pc65 | pc66 | pc67 | pc68 | pc69 | pc70 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Standard deviation | 14912.090624 | 6365.402970 | 4101.434915 | 2600.961311 | 1625.477034 | 1204.577424 | 1011.360523 | 963.102042 | 573.311672 | ... | 35.103439 | 34.577217 | 33.492329 | 32.860702 | 31.849359 | 30.027758 | 29.474500 | 28.783870 | 27.887428 | 25.663299 |
| 1 | Proportion of Variance | 0.752634 | 0.137138 | 0.056935 | 0.022897 | 0.008943 | 0.004911 | 0.003462 | 0.003139 | 0.001112 | ... | 0.000004 | 0.000004 | 0.000004 | 0.000004 | 0.000003 | 0.000003 | 0.000003 | 0.000003 | 0.000003 | 0.000002 |
| 2 | Cumulative Proportion | 0.752634 | 0.889772 | 0.946707 | 0.969603 | 0.978546 | 0.983457 | 0.986919 | 0.990059 | 0.991171 | ... | 0.999946 | 0.999951 | 0.999954 | 0.999958 | 0.999961 | 0.999964 | 0.999967 | 0.999970 | 0.999973 | 0.999975 |
3 rows × 71 columns
df_OS_new = df2.pca.predict(df2)
pca prediction progress: |███████████████████████████████████████████████████████| (done) 100%
df_OS_new.shape
(2031, 70)
df_OS_new
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | PC11 | PC12 | PC13 | PC14 | PC15 | PC16 | PC17 | PC18 | PC19 | PC20 | PC21 | PC22 | PC23 | PC24 | PC25 | PC26 | PC27 | PC28 | PC29 | PC30 | PC31 | PC32 | PC33 | PC34 | PC35 | PC36 | PC37 | PC38 | PC39 | PC40 | PC41 | PC42 | PC43 | PC44 | PC45 | PC46 | PC47 | PC48 | PC49 | PC50 | PC51 | PC52 | PC53 | PC54 | PC55 | PC56 | PC57 | PC58 | PC59 | PC60 | PC61 | PC62 | PC63 | PC64 | PC65 | PC66 | PC67 | PC68 | PC69 | PC70 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 595.151 | -27.1322 | -117.111 | 16.2053 | -392.475 | 365.31 | -254.216 | -411.291 | -390.749 | -651.739 | -134.968 | 746.509 | -299.86 | 85.2949 | -477.051 | 609.342 | -373.849 | 694.846 | 867.802 | 1003.89 | -563.052 | -492.231 | -711.611 | -1032.4 | 156.048 | 342.831 | -1394.34 | -222.089 | -1387.98 | -11.9583 | 344.467 | -6152.49 | -1812.61 | -198.033 | -2711.55 | -2601.37 | -535.619 | 162.576 | 450.661 | 921.601 | -71.5662 | 114.419 | 228.975 | 170.933 | -72.5911 | -242.671 | 32.0516 | -17.8851 | 8.76553 | 85.0397 | 36.6773 | -83.4441 | 27.9831 | 8.77142 | 5.96324 | 4.9257 | 14.5061 | -16.3669 | 30.9917 | 13.8063 | -36.4637 | 24.6291 | -6.47006 | -4.30772 | 17.4621 | -5.29104 | 30.8561 | 4.44873 | 1.49169 | -6.48971 |
| 11859.9 | 4356.73 | -442.214 | 560.124 | -5928.6 | 3554.37 | 230.725 | -268.76 | 541.052 | -523.548 | 148.758 | 405.46 | 110.918 | 83.9098 | -52.0172 | 359.505 | -216.681 | -102.125 | -508.674 | 5.68512 | 239.059 | -13.4145 | -76.6042 | 21.9323 | 416.686 | -199.933 | 112.326 | 76.3903 | 159.604 | 25.0546 | -134.074 | -196.49 | -332.053 | -92.1799 | 30.1924 | 316.104 | 28.6229 | 68.5312 | -227.039 | 49.1506 | -36.0055 | -16.0328 | -73.582 | -142.642 | 102.124 | -28.6603 | 28.908 | 1.36742 | 17.9755 | -10.9543 | -27.0952 | 93.1898 | 12.3125 | -13.761 | -25.3888 | -146.681 | 92.4286 | -86.6724 | 113.094 | 64.1652 | 18.6626 | -2.59741 | 19.2339 | 32.6142 | -20.8801 | -1.64769 | 5.44796 | -7.57308 | 12.0555 | 17.7453 |
| 17932.1 | -7779.81 | 4255.57 | 943.637 | -451.696 | -302.534 | 228.633 | 28.2479 | 978.441 | -1205.45 | 1170.42 | 50.7894 | 28.6129 | 12.4087 | -673.682 | 467.06 | -88.1018 | 271.367 | 176.104 | -57.1708 | 136.644 | 329.865 | 18.5849 | 141.774 | 312.318 | 254.403 | 98.2715 | 334.62 | 556.642 | 90.3778 | -87.3502 | -27.7761 | 22.2919 | -122.282 | -193.345 | 65.5873 | -132.445 | 45.1812 | -53.8708 | -70.0876 | 13.6046 | 65.3726 | 70.7075 | 0.770533 | 27.9268 | -35.4671 | 141.772 | -109.653 | 53.2576 | 41.8683 | -65.1957 | -20.8157 | 10.5377 | -4.82925 | -23.8353 | 31.8527 | -68.7987 | -5.22425 | -69.96 | -63.2274 | 31.8811 | 17.4291 | 31.636 | 7.24512 | 17.8713 | 6.53981 | 19.6229 | -17.0549 | -2.58405 | -40.9885 |
| 11889.4 | 5697.84 | 4049.59 | 1791.59 | 278.19 | 1091.2 | -864.017 | 33.9153 | 421.008 | 771.773 | -355.894 | -318.193 | -40.3507 | -87.6001 | 60.2154 | 222.869 | 9.61034 | 8.75599 | -424.605 | 2.4274 | -292.677 | 347.858 | 645.86 | -20.0528 | -58.0168 | 87.4087 | 131.145 | -218.926 | 339.704 | 22.7857 | 54.6786 | -203.197 | 127.669 | 88.1995 | 209.08 | -111.296 | -40.592 | 50.5221 | 31.964 | 0.0846031 | 19.3547 | -255.423 | 198.329 | 43.4134 | -131.57 | -18.8084 | -33.7339 | 70.4975 | -80.5652 | -43.985 | -66.0822 | 3.07404 | -3.31217 | -10.1777 | -41.4094 | -72.9775 | -78.1864 | -42.5201 | 4.29671 | -28.0646 | -9.07542 | 31.0742 | -30.107 | 5.65899 | 1.76561 | -19.9286 | 23.9494 | -2.15368 | 80.8299 | 15.3532 |
| 13998.3 | 3015.04 | 1781.23 | -1198.59 | -322.747 | 49.3907 | 590.539 | 73.9974 | 136.974 | 48.0897 | -104.856 | -146.536 | -11.4753 | -0.806239 | -495.442 | 27.6658 | -145.772 | -398.689 | -349.738 | 823.014 | -41.3632 | -123.945 | 127.093 | -335.195 | -108.02 | -512.869 | 331.029 | 294.556 | -97.5135 | -183.574 | -16.8311 | 22.9045 | 39.2586 | 27.5793 | -58.6956 | 22.1226 | -3.29234 | 92.0124 | -88.9115 | 32.5767 | -2.92504 | -55.3788 | 39.8091 | -14.9766 | 13.1046 | -18.9245 | 109.067 | -9.37523 | 48.5873 | 16.1365 | -52.4296 | -26.4093 | 30.7128 | 26.5231 | -13.9454 | 14.0908 | 39.8864 | -17.5702 | -34.9778 | -32.4896 | -21.3419 | -1.06611 | -31.3735 | -15.3616 | 40.685 | -5.03452 | -7.52215 | -20.1451 | -7.76322 | -3.72149 |
| 29904.1 | -29729.2 | 1175.36 | -611.078 | 680.991 | 804.704 | 764.309 | -215.356 | 170.637 | 260.625 | -171.652 | 228.406 | -95.125 | -404.162 | 62.8464 | 450.584 | 490.244 | -375.995 | 85.061 | -87.1745 | 58.7772 | 149.391 | -16.838 | 316.402 | 376.492 | -315.632 | 37.5914 | -310.065 | 389.523 | 149.031 | 71.6377 | -125.02 | 236.037 | 59.7614 | -35.6637 | -32.4363 | -166.014 | 9.49577 | -32.3199 | -21.9934 | 9.4915 | 176.105 | -18.7039 | -10.1741 | 33.2748 | -17.069 | -75.322 | -55.0344 | -38.8813 | 10.8278 | 23.0063 | 24.1013 | -42.0393 | -16.6993 | 14.9999 | 13.8488 | -58.321 | -48.8372 | 70.9139 | -11.1655 | 15.2467 | 1.24785 | 7.45807 | -38.0272 | -15.8308 | -23.1033 | 12.4922 | -12.8759 | 25.7272 | 8.86152 |
| 12017.2 | 3909.84 | 3250.07 | -191.369 | 96.7798 | -874.948 | 126.724 | 168.42 | -105.923 | -658.496 | 340.327 | 483.1 | -87.5864 | -270.933 | 487.438 | 339.664 | 243.588 | 242.116 | 179.443 | -7.93778 | -302.349 | -65.058 | 180.403 | 224.34 | 79.0817 | -50.5741 | 4.45818 | 56.1217 | -157.572 | -182.119 | 100.715 | -27.9575 | -60.4703 | -89.7928 | -12.7501 | 111.755 | 53.4153 | 5.1793 | -80.7878 | -28.974 | -25.4955 | 52.937 | -59.4061 | -0.0076895 | -24.8425 | -16.1079 | 95.8862 | 42.7634 | -88.4848 | -35.4771 | -19.0283 | 12.2783 | -11.2796 | -9.48177 | -14.1081 | -10.5111 | -48.4583 | -50.933 | -26.7227 | 2.95608 | 36.9635 | 1.75753 | 5.76168 | 30.7614 | -45.1496 | 13.7352 | 46.5516 | 14.7975 | -31.8923 | 7.10239 |
| 21737 | -16310.8 | 3460.38 | 7110.47 | -234.181 | -294.044 | 434.547 | 131.181 | -216.194 | 1.2751 | -183.462 | -590.43 | -85.9635 | -18.7919 | 121.271 | 40.8778 | -57.1103 | -491.503 | -112.106 | -397.712 | 120.236 | -156.57 | -588.231 | -287.384 | 81.013 | -170.576 | 4.73449 | 128.637 | 147.367 | -139.44 | 262.162 | 201.573 | -73.5589 | 68.5667 | -141.196 | -166.469 | 1.21065 | -1.72149 | 53.3865 | 151.162 | 67.0116 | 148.386 | -104.485 | -113.607 | 66.1012 | -31.08 | -69.7532 | -56.6741 | -107.277 | -28.562 | 50.6591 | -9.63078 | -38.5489 | -0.873862 | -28.2492 | 3.58965 | -36.0091 | -10.5358 | 27.4667 | -26.9383 | -30.2464 | 16.7414 | 33.1234 | -36.5494 | 16.6781 | -15.9847 | -27.665 | 3.03551 | 25.2878 | 45.6773 |
| 12342.9 | 3569.21 | 2776.13 | -171.397 | -305.212 | -279.582 | 2.52426 | 182.293 | -363.184 | -92.9426 | -198.221 | -279.004 | -178.577 | -0.722844 | 275.123 | 891.351 | -925.868 | 130.73 | -216.782 | 436.72 | 14.1053 | -570.027 | -317.435 | 130.168 | 181.417 | -114.173 | 393.52 | 293.526 | 90.8051 | -93.617 | 99.8074 | 28.0275 | 218.176 | -53.3229 | -187.403 | 61.6348 | 12.0114 | 44.9009 | -123.277 | -17.2015 | -6.29438 | 105.869 | 40.9092 | 23.9927 | -12.7843 | -75.8856 | 24.9925 | -30.2291 | 60.0583 | 9.56427 | 12.7711 | 46.4706 | -40.9509 | 2.63083 | 22.8329 | 45.25 | 6.97432 | -7.75177 | 28.2614 | 49.5655 | -17.9804 | -6.12762 | 59.6029 | 7.93644 | 28.7505 | -0.83348 | 44.9755 | 3.16501 | -28.2642 | 2.97124 |
| 14219.2 | 5030.66 | -2380.94 | -1622.27 | 1199.23 | 109.017 | 491.567 | 118.709 | -90.5728 | -3.17591 | -222.738 | -112.683 | -133.408 | -210.347 | -256.204 | 74.317 | -308.737 | -15.3433 | -230.378 | -197.321 | 354.475 | -287.87 | 285.662 | 96.2022 | 112.375 | 189.825 | -136.429 | -255.374 | 157.005 | 148.273 | 111.484 | -15.1394 | 321.928 | 20.0582 | -15.6582 | -96.1224 | -134.989 | 16.1519 | -35.2557 | 52.1799 | -0.656532 | 7.61206 | 53.454 | 36.9503 | 26.7891 | -5.51114 | 71.4356 | 140.845 | -22.41 | -22.5467 | -17.7952 | -40.1342 | -35.8179 | 5.68161 | -12.2681 | -20.4492 | 13.2539 | 6.04934 | -39.7277 | 25.6652 | -44.1591 | -11.7527 | -5.92715 | 41.1834 | 25.3924 | 12.4417 | -4.70622 | 5.92725 | 44.7808 | -6.32249 |
from h2o.estimators.naive_bayes import H2ONaiveBayesEstimator
nv = H2ONaiveBayesEstimator()
df_OS_new2 = df_OS_new.cbind(df2[response2])
df_OS_new2
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | PC11 | PC12 | PC13 | PC14 | PC15 | PC16 | PC17 | PC18 | PC19 | PC20 | PC21 | PC22 | PC23 | PC24 | PC25 | PC26 | PC27 | PC28 | PC29 | PC30 | PC31 | PC32 | PC33 | PC34 | PC35 | PC36 | PC37 | PC38 | PC39 | PC40 | PC41 | PC42 | PC43 | PC44 | PC45 | PC46 | PC47 | PC48 | PC49 | PC50 | PC51 | PC52 | PC53 | PC54 | PC55 | PC56 | PC57 | PC58 | PC59 | PC60 | PC61 | PC62 | PC63 | PC64 | PC65 | PC66 | PC67 | PC68 | PC69 | PC70 | C591 | C1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 595.151 | -27.1322 | -117.111 | 16.2053 | -392.475 | 365.31 | -254.216 | -411.291 | -390.749 | -651.739 | -134.968 | 746.509 | -299.86 | 85.2949 | -477.051 | 609.342 | -373.849 | 694.846 | 867.802 | 1003.89 | -563.052 | -492.231 | -711.611 | -1032.4 | 156.048 | 342.831 | -1394.34 | -222.089 | -1387.98 | -11.9583 | 344.467 | -6152.49 | -1812.61 | -198.033 | -2711.55 | -2601.37 | -535.619 | 162.576 | 450.661 | 921.601 | -71.5662 | 114.419 | 228.975 | 170.933 | -72.5911 | -242.671 | 32.0516 | -17.8851 | 8.76553 | 85.0397 | 36.6773 | -83.4441 | 27.9831 | 8.77142 | 5.96324 | 4.9257 | 14.5061 | -16.3669 | 30.9917 | 13.8063 | -36.4637 | 24.6291 | -6.47006 | -4.30772 | 17.4621 | -5.29104 | 30.8561 | 4.44873 | 1.49169 | -6.48971 | 99 | nan |
| 11859.9 | 4356.73 | -442.214 | 560.124 | -5928.6 | 3554.37 | 230.725 | -268.76 | 541.052 | -523.548 | 148.758 | 405.46 | 110.918 | 83.9098 | -52.0172 | 359.505 | -216.681 | -102.125 | -508.674 | 5.68512 | 239.059 | -13.4145 | -76.6042 | 21.9323 | 416.686 | -199.933 | 112.326 | 76.3903 | 159.604 | 25.0546 | -134.074 | -196.49 | -332.053 | -92.1799 | 30.1924 | 316.104 | 28.6229 | 68.5312 | -227.039 | 49.1506 | -36.0055 | -16.0328 | -73.582 | -142.642 | 102.124 | -28.6603 | 28.908 | 1.36742 | 17.9755 | -10.9543 | -27.0952 | 93.1898 | 12.3125 | -13.761 | -25.3888 | -146.681 | 92.4286 | -86.6724 | 113.094 | 64.1652 | 18.6626 | -2.59741 | 19.2339 | 32.6142 | -20.8801 | -1.64769 | 5.44796 | -7.57308 | 12.0555 | 17.7453 | 0.0381 | 1 |
| 17932.1 | -7779.81 | 4255.57 | 943.637 | -451.696 | -302.534 | 228.633 | 28.2479 | 978.441 | -1205.45 | 1170.42 | 50.7894 | 28.6129 | 12.4087 | -673.682 | 467.06 | -88.1018 | 271.367 | 176.104 | -57.1708 | 136.644 | 329.865 | 18.5849 | 141.774 | 312.318 | 254.403 | 98.2715 | 334.62 | 556.642 | 90.3778 | -87.3502 | -27.7761 | 22.2919 | -122.282 | -193.345 | 65.5873 | -132.445 | 45.1812 | -53.8708 | -70.0876 | 13.6046 | 65.3726 | 70.7075 | 0.770533 | 27.9268 | -35.4671 | 141.772 | -109.653 | 53.2576 | 41.8683 | -65.1957 | -20.8157 | 10.5377 | -4.82925 | -23.8353 | 31.8527 | -68.7987 | -5.22425 | -69.96 | -63.2274 | 31.8811 | 17.4291 | 31.636 | 7.24512 | 17.8713 | 6.53981 | 19.6229 | -17.0549 | -2.58405 | -40.9885 | 0.026 | -1 |
| 11889.4 | 5697.84 | 4049.59 | 1791.59 | 278.19 | 1091.2 | -864.017 | 33.9153 | 421.008 | 771.773 | -355.894 | -318.193 | -40.3507 | -87.6001 | 60.2154 | 222.869 | 9.61034 | 8.75599 | -424.605 | 2.4274 | -292.677 | 347.858 | 645.86 | -20.0528 | -58.0168 | 87.4087 | 131.145 | -218.926 | 339.704 | 22.7857 | 54.6786 | -203.197 | 127.669 | 88.1995 | 209.08 | -111.296 | -40.592 | 50.5221 | 31.964 | 0.0846031 | 19.3547 | -255.423 | 198.329 | 43.4134 | -131.57 | -18.8084 | -33.7339 | 70.4975 | -80.5652 | -43.985 | -66.0822 | 3.07404 | -3.31217 | -10.1777 | -41.4094 | -72.9775 | -78.1864 | -42.5201 | 4.29671 | -28.0646 | -9.07542 | 31.0742 | -30.107 | 5.65899 | 1.76561 | -19.9286 | 23.9494 | -2.15368 | 80.8299 | 15.3532 | 0.0558 | -1 |
| 13998.3 | 3015.04 | 1781.23 | -1198.59 | -322.747 | 49.3907 | 590.539 | 73.9974 | 136.974 | 48.0897 | -104.856 | -146.536 | -11.4753 | -0.806239 | -495.442 | 27.6658 | -145.772 | -398.689 | -349.738 | 823.014 | -41.3632 | -123.945 | 127.093 | -335.195 | -108.02 | -512.869 | 331.029 | 294.556 | -97.5135 | -183.574 | -16.8311 | 22.9045 | 39.2586 | 27.5793 | -58.6956 | 22.1226 | -3.29234 | 92.0124 | -88.9115 | 32.5767 | -2.92504 | -55.3788 | 39.8091 | -14.9766 | 13.1046 | -18.9245 | 109.067 | -9.37523 | 48.5873 | 16.1365 | -52.4296 | -26.4093 | 30.7128 | 26.5231 | -13.9454 | 14.0908 | 39.8864 | -17.5702 | -34.9778 | -32.4896 | -21.3419 | -1.06611 | -31.3735 | -15.3616 | 40.685 | -5.03452 | -7.52215 | -20.1451 | -7.76322 | -3.72149 | 0.0632 | -1 |
| 29904.1 | -29729.2 | 1175.36 | -611.078 | 680.991 | 804.704 | 764.309 | -215.356 | 170.637 | 260.625 | -171.652 | 228.406 | -95.125 | -404.162 | 62.8464 | 450.584 | 490.244 | -375.995 | 85.061 | -87.1745 | 58.7772 | 149.391 | -16.838 | 316.402 | 376.492 | -315.632 | 37.5914 | -310.065 | 389.523 | 149.031 | 71.6377 | -125.02 | 236.037 | 59.7614 | -35.6637 | -32.4363 | -166.014 | 9.49577 | -32.3199 | -21.9934 | 9.4915 | 176.105 | -18.7039 | -10.1741 | 33.2748 | -17.069 | -75.322 | -55.0344 | -38.8813 | 10.8278 | 23.0063 | 24.1013 | -42.0393 | -16.6993 | 14.9999 | 13.8488 | -58.321 | -48.8372 | 70.9139 | -11.1655 | 15.2467 | 1.24785 | 7.45807 | -38.0272 | -15.8308 | -23.1033 | 12.4922 | -12.8759 | 25.7272 | 8.86152 | 0.0381 | -1 |
| 12017.2 | 3909.84 | 3250.07 | -191.369 | 96.7798 | -874.948 | 126.724 | 168.42 | -105.923 | -658.496 | 340.327 | 483.1 | -87.5864 | -270.933 | 487.438 | 339.664 | 243.588 | 242.116 | 179.443 | -7.93778 | -302.349 | -65.058 | 180.403 | 224.34 | 79.0817 | -50.5741 | 4.45818 | 56.1217 | -157.572 | -182.119 | 100.715 | -27.9575 | -60.4703 | -89.7928 | -12.7501 | 111.755 | 53.4153 | 5.1793 | -80.7878 | -28.974 | -25.4955 | 52.937 | -59.4061 | -0.0076895 | -24.8425 | -16.1079 | 95.8862 | 42.7634 | -88.4848 | -35.4771 | -19.0283 | 12.2783 | -11.2796 | -9.48177 | -14.1081 | -10.5111 | -48.4583 | -50.933 | -26.7227 | 2.95608 | 36.9635 | 1.75753 | 5.76168 | 30.7614 | -45.1496 | 13.7352 | 46.5516 | 14.7975 | -31.8923 | 7.10239 | 0.0409 | 1 |
| 21737 | -16310.8 | 3460.38 | 7110.47 | -234.181 | -294.044 | 434.547 | 131.181 | -216.194 | 1.2751 | -183.462 | -590.43 | -85.9635 | -18.7919 | 121.271 | 40.8778 | -57.1103 | -491.503 | -112.106 | -397.712 | 120.236 | -156.57 | -588.231 | -287.384 | 81.013 | -170.576 | 4.73449 | 128.637 | 147.367 | -139.44 | 262.162 | 201.573 | -73.5589 | 68.5667 | -141.196 | -166.469 | 1.21065 | -1.72149 | 53.3865 | 151.162 | 67.0116 | 148.386 | -104.485 | -113.607 | 66.1012 | -31.08 | -69.7532 | -56.6741 | -107.277 | -28.562 | 50.6591 | -9.63078 | -38.5489 | -0.873862 | -28.2492 | 3.58965 | -36.0091 | -10.5358 | 27.4667 | -26.9383 | -30.2464 | 16.7414 | 33.1234 | -36.5494 | 16.6781 | -15.9847 | -27.665 | 3.03551 | 25.2878 | 45.6773 | -0.0028 | -1 |
| 12342.9 | 3569.21 | 2776.13 | -171.397 | -305.212 | -279.582 | 2.52426 | 182.293 | -363.184 | -92.9426 | -198.221 | -279.004 | -178.577 | -0.722844 | 275.123 | 891.351 | -925.868 | 130.73 | -216.782 | 436.72 | 14.1053 | -570.027 | -317.435 | 130.168 | 181.417 | -114.173 | 393.52 | 293.526 | 90.8051 | -93.617 | 99.8074 | 28.0275 | 218.176 | -53.3229 | -187.403 | 61.6348 | 12.0114 | 44.9009 | -123.277 | -17.2015 | -6.29438 | 105.869 | 40.9092 | 23.9927 | -12.7843 | -75.8856 | 24.9925 | -30.2291 | 60.0583 | 9.56427 | 12.7711 | 46.4706 | -40.9509 | 2.63083 | 22.8329 | 45.25 | 6.97432 | -7.75177 | 28.2614 | 49.5655 | -17.9804 | -6.12762 | 59.6029 | 7.93644 | 28.7505 | -0.83348 | 44.9755 | 3.16501 | -28.2642 | 2.97124 | -0.0233 | -1 |
| 14219.2 | 5030.66 | -2380.94 | -1622.27 | 1199.23 | 109.017 | 491.567 | 118.709 | -90.5728 | -3.17591 | -222.738 | -112.683 | -133.408 | -210.347 | -256.204 | 74.317 | -308.737 | -15.3433 | -230.378 | -197.321 | 354.475 | -287.87 | 285.662 | 96.2022 | 112.375 | 189.825 | -136.429 | -255.374 | 157.005 | 148.273 | 111.484 | -15.1394 | 321.928 | 20.0582 | -15.6582 | -96.1224 | -134.989 | 16.1519 | -35.2557 | 52.1799 | -0.656532 | 7.61206 | 53.454 | 36.9503 | 26.7891 | -5.51114 | 71.4356 | 140.845 | -22.41 | -22.5467 | -17.7952 | -40.1342 | -35.8179 | 5.68161 | -12.2681 | -20.4492 | 13.2539 | 6.04934 | -39.7277 | 25.6652 | -44.1591 | -11.7527 | -5.92715 | 41.1834 | 25.3924 | 12.4417 | -4.70622 | 5.92725 | 44.7808 | -6.32249 | -0.0595 | -1 |
h2o.download_csv(df_OS_new2,"C:\\Users\\Admin\\Desktop\\FMT")
'C:\\Users\\Admin\\Desktop\\FMT\\unknown'
pca_df3 = pd.read_csv('PCA_OS.csv')
print(pca_df3.shape)
pca_df3.head()
(2031, 71)
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | ... | PC62 | PC63 | PC64 | PC65 | PC66 | PC67 | PC68 | PC69 | PC70 | C1 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 595.150843 | -27.132215 | -117.111369 | 16.205333 | -392.474651 | 365.310215 | -254.215808 | -411.290998 | -390.748623 | -651.738746 | ... | 24.629118 | -6.470057 | -4.307722 | 17.462143 | -5.291037 | 30.856133 | 4.448725 | 1.491692 | -6.489714 | -1 |
| 1 | 11859.899180 | 4356.730990 | -442.214147 | 560.123607 | -5928.602833 | 3554.366855 | 230.724940 | -268.759962 | 541.052297 | -523.547869 | ... | -2.597408 | 19.233925 | 32.614245 | -20.880149 | -1.647686 | 5.447959 | -7.573077 | 12.055456 | 17.745269 | 1 |
| 2 | 17932.089940 | -7779.807266 | 4255.567850 | 943.637083 | -451.695663 | -302.534247 | 228.632968 | 28.247905 | 978.440502 | -1205.448989 | ... | 17.429125 | 31.635952 | 7.245118 | 17.871319 | 6.539815 | 19.622927 | -17.054874 | -2.584047 | -40.988523 | -1 |
| 3 | 11889.449630 | 5697.842830 | 4049.591117 | 1791.585395 | 278.189721 | 1091.201865 | -864.017224 | 33.915301 | 421.008007 | 771.773231 | ... | 31.074214 | -30.107047 | 5.658991 | 1.765605 | -19.928562 | 23.949436 | -2.153675 | 80.829917 | 15.353174 | -1 |
| 4 | 13998.300790 | 3015.038683 | 1781.229854 | -1198.593467 | -322.746695 | 49.390713 | 590.538542 | 73.997425 | 136.973808 | 48.089697 | ... | -1.066112 | -31.373505 | -15.361560 | 40.684988 | -5.034515 | -7.522152 | -20.145066 | -7.763225 | -3.721486 | -1 |
5 rows × 71 columns
pca_df3.dtypes
PC1 float64
PC2 float64
PC3 float64
PC4 float64
PC5 float64
...
PC67 float64
PC68 float64
PC69 float64
PC70 float64
C1 int64
Length: 71, dtype: object
pca_df3['C1'] = pca_df3['C1'].apply(str)
print()
print(pca_df3.dtypes)
pca_df3
PC1 float64
PC2 float64
PC3 float64
PC4 float64
PC5 float64
...
PC67 float64
PC68 float64
PC69 float64
PC70 float64
C1 object
Length: 71, dtype: object
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | ... | PC62 | PC63 | PC64 | PC65 | PC66 | PC67 | PC68 | PC69 | PC70 | C1 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 595.150843 | -27.132215 | -117.111369 | 16.205333 | -392.474651 | 365.310215 | -254.215808 | -411.290998 | -390.748623 | -651.738746 | ... | 24.629118 | -6.470057 | -4.307722 | 17.462143 | -5.291037 | 30.856133 | 4.448725 | 1.491692 | -6.489714 | -1 |
| 1 | 11859.899180 | 4356.730990 | -442.214147 | 560.123607 | -5928.602833 | 3554.366855 | 230.724940 | -268.759962 | 541.052297 | -523.547869 | ... | -2.597408 | 19.233925 | 32.614245 | -20.880149 | -1.647686 | 5.447959 | -7.573077 | 12.055456 | 17.745269 | 1 |
| 2 | 17932.089940 | -7779.807266 | 4255.567850 | 943.637083 | -451.695663 | -302.534247 | 228.632968 | 28.247905 | 978.440502 | -1205.448989 | ... | 17.429125 | 31.635952 | 7.245118 | 17.871319 | 6.539815 | 19.622927 | -17.054874 | -2.584047 | -40.988523 | -1 |
| 3 | 11889.449630 | 5697.842830 | 4049.591117 | 1791.585395 | 278.189721 | 1091.201865 | -864.017224 | 33.915301 | 421.008007 | 771.773231 | ... | 31.074214 | -30.107047 | 5.658991 | 1.765605 | -19.928562 | 23.949436 | -2.153675 | 80.829917 | 15.353174 | -1 |
| 4 | 13998.300790 | 3015.038683 | 1781.229854 | -1198.593467 | -322.746695 | 49.390713 | 590.538542 | 73.997425 | 136.973808 | 48.089697 | ... | -1.066112 | -31.373505 | -15.361560 | 40.684988 | -5.034515 | -7.522152 | -20.145066 | -7.763225 | -3.721486 | -1 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 2026 | 15420.634170 | 2943.805714 | -1601.224113 | -398.056120 | 1224.005424 | 663.477503 | 996.684174 | 116.970955 | -399.791457 | -275.218065 | ... | -3.448809 | 5.732685 | -1.914337 | -7.180851 | 1.140562 | -3.244497 | -17.240733 | 11.237279 | 6.024569 | 1 |
| 2027 | 11956.223460 | 5669.647767 | 2356.437653 | 1856.915996 | 855.324126 | 27.234000 | -692.129970 | 179.886978 | 212.245361 | 46.024487 | ... | 0.684106 | 38.561159 | 51.853832 | 8.547109 | -12.767562 | -33.255045 | -0.508393 | -24.859467 | -21.950524 | 1 |
| 2028 | 17029.711020 | -5244.065440 | 2310.357763 | -4642.255781 | 472.896075 | -185.801308 | 298.151988 | -9.448559 | 267.538963 | -20.311445 | ... | 4.674001 | 1.250119 | 3.735790 | 7.189823 | 0.191968 | 14.941931 | 13.086769 | -3.849298 | 24.251682 | 1 |
| 2029 | 11929.505130 | 4520.307331 | 1215.974790 | 264.140714 | 262.511077 | -847.678583 | -664.880337 | 195.561200 | -357.008493 | 149.074432 | ... | 1.304950 | -66.449364 | 17.609408 | -8.825900 | -8.430786 | -2.565917 | 24.332191 | 17.679096 | 4.177392 | 1 |
| 2030 | 12814.309170 | 5620.736909 | 175.896663 | 336.636201 | 621.382548 | 392.566822 | 1013.667695 | 131.936304 | -367.677615 | -347.411337 | ... | -3.654326 | 12.770717 | 25.276717 | -29.973833 | 11.767549 | 27.608943 | -17.339712 | -30.268387 | -16.182827 | 1 |
2031 rows × 71 columns
pca_df4= pca_df3.drop('C1', axis=1)
y = pca_df3['C1']
X = pca_df4
classifier = Classification(
predictor='svm',
params= {},
cv_folds=2,
epochs=5)
classifier.fit(X, y)
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Started LuciferML
Checking if labels or features are categorical! [*]
Features are not categorical [ ✓ ]
Labels are Categorical [*]
Encoding Labels
Encoding Labels Done [ ✓ ]
Checking for Categorical Variables Done [ ✓ ]
Checking for Sparse Matrix [*]
Splitting Data into Train and Validation Sets [*]
Splitting Done [ ✓ ]
Scaling Training and Test Sets [*]
Scaling Done [ ✓ ]
Training Support Vector Machine on Training Set [*]
Model Training Done [ ✓ ]
Predicting Data [*]
Data Prediction Done [ ✓ ]
Making Confusion Matrix [*]
[[186 6]
[ 0 215]]
Confusion Matrix Done [ ✓ ] Evaluating Model Performance [*] Validation Accuracy is : 0.9852579852579852 Evaluating Model Performance [ ✓ ] Applying K-Fold Cross Validation [*] Accuracy: 93.10 % Standard Deviation: 1.48 % K-Fold Cross Validation [ ✓ ] Complete [ ✓ ] Time Elapsed : 1.382007360458374 seconds
from h2o.estimators.pca import H2OPrincipalComponentAnalysisEstimator
df10 = h2o.import_file("C:\\Users\\Admin\\Desktop\\FMT\\US.csv")
df10.pca = H2OPrincipalComponentAnalysisEstimator(k=30)
response10 = "C1"
fm10 = df10.col_names
fm10.remove(response)
Parse progress: |████████████████████████████████████████████████████████████████| (done) 100%
df10.pca.train(x=fm10, training_frame=df10)
pca Model Build progress: |██████████████████████████████████████████████████████| (done) 100% Model Details ============= H2OPrincipalComponentAnalysisEstimator : Principal Components Analysis Model Key: PCA_model_python_1638771670270_14 Importance of components:
| pc1 | pc2 | pc3 | pc4 | pc5 | pc6 | pc7 | pc8 | pc9 | ... | pc21 | pc22 | pc23 | pc24 | pc25 | pc26 | pc27 | pc28 | pc29 | pc30 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Standard deviation | 16826.660607 | 7141.607671 | 5633.216250 | 3604.831221 | 1809.942460 | 1653.929756 | 1297.314731 | 1191.221668 | 837.312653 | ... | 243.678447 | 233.905439 | 217.626109 | 201.764188 | 199.709050 | 190.896019 | 182.105753 | 178.300661 | 169.190590 | 153.426031 |
| 1 | Proportion of Variance | 0.724702 | 0.130544 | 0.081223 | 0.033261 | 0.008385 | 0.007002 | 0.004308 | 0.003632 | 0.001794 | ... | 0.000152 | 0.000140 | 0.000121 | 0.000104 | 0.000102 | 0.000093 | 0.000085 | 0.000081 | 0.000073 | 0.000060 |
| 2 | Cumulative Proportion | 0.724702 | 0.855246 | 0.936469 | 0.969729 | 0.978114 | 0.985116 | 0.989424 | 0.993056 | 0.994850 | ... | 0.998644 | 0.998784 | 0.998906 | 0.999010 | 0.999112 | 0.999205 | 0.999290 | 0.999371 | 0.999445 | 0.999505 |
3 rows × 31 columns
ModelMetricsPCA: pca ** Reported on train data. ** MSE: NaN RMSE: NaN Scoring History for GramSVD:
| timestamp | duration | iterations | ||
|---|---|---|---|---|
| 0 | 2021-12-06 19:26:17 | 0.895 sec | 0.0 |
df10
| C1 | C2 | C3 | C4 | C5 | C6 | C7 | C8 | C9 | C10 | C11 | C12 | C13 | C14 | C15 | C16 | C17 | C18 | C19 | C20 | C21 | C22 | C23 | C24 | C25 | C26 | C27 | C28 | C29 | C30 | C31 | C32 | C33 | C34 | C35 | C36 | C37 | C38 | C39 | C40 | C41 | C42 | C43 | C44 | C45 | C46 | C47 | C48 | C49 | C50 | C51 | C52 | C53 | C54 | C55 | C56 | C57 | C58 | C59 | C60 | C61 | C62 | C63 | C64 | C65 | C66 | C67 | C68 | C69 | C70 | C71 | C72 | C73 | C74 | C75 | C76 | C77 | C78 | C79 | C80 | C81 | C82 | C83 | C84 | C85 | C86 | C87 | C88 | C89 | C90 | C91 | C92 | C93 | C94 | C95 | C96 | C97 | C98 | C99 | C100 | C101 | C102 | C103 | C104 | C105 | C106 | C107 | C108 | C109 | C110 | C111 | C112 | C113 | C114 | C115 | C116 | C117 | C118 | C119 | C120 | C121 | C122 | C123 | C124 | C125 | C126 | C127 | C128 | C129 | C130 | C131 | C132 | C133 | C134 | C135 | C136 | C137 | C138 | C139 | C140 | C141 | C142 | C143 | C144 | C145 | C146 | C147 | C148 | C149 | C150 | C151 | C152 | C153 | C154 | C155 | C156 | C157 | C158 | C159 | C160 | C161 | C162 | C163 | C164 | C165 | C166 | C167 | C168 | C169 | C170 | C171 | C172 | C173 | C174 | C175 | C176 | C177 | C178 | C179 | C180 | C181 | C182 | C183 | C184 | C185 | C186 | C187 | C188 | C189 | C190 | C191 | C192 | C193 | C194 | C195 | C196 | C197 | C198 | C199 | C200 | C201 | C202 | C203 | C204 | C205 | C206 | C207 | C208 | C209 | C210 | C211 | C212 | C213 | C214 | C215 | C216 | C217 | C218 | C219 | C220 | C221 | C222 | C223 | C224 | C225 | C226 | C227 | C228 | C229 | C230 | C231 | C232 | C233 | C234 | C235 | C236 | C237 | C238 | C239 | C240 | C241 | C242 | C243 | C244 | C245 | C246 | C247 | C248 | C249 | C250 | C251 | C252 | C253 | C254 | C255 | C256 | C257 | C258 | C259 | C260 | C261 | C262 | C263 | C264 | C265 | C266 | C267 | C268 | C269 | C270 | C271 | C272 | C273 | C274 | C275 | C276 | C277 | C278 | C279 | C280 | C281 | C282 | C283 | C284 | C285 | C286 | C287 | C288 | C289 | C290 | C291 | C292 | C293 | C294 | C295 | C296 | C297 | C298 | C299 | C300 | C301 | C302 | C303 | C304 | C305 | C306 | C307 | C308 | C309 | C310 | C311 | C312 | C313 | C314 | C315 | C316 | C317 | C318 | C319 | C320 | C321 | C322 | C323 | C324 | C325 | C326 | C327 | C328 | C329 | C330 | C331 | C332 | C333 | C334 | C335 | C336 | C337 | C338 | C339 | C340 | C341 | C342 | C343 | C344 | C345 | C346 | C347 | C348 | C349 | C350 | C351 | C352 | C353 | C354 | C355 | C356 | C357 | C358 | C359 | C360 | C361 | C362 | C363 | C364 | C365 | C366 | C367 | C368 | C369 | C370 | C371 | C372 | C373 | C374 | C375 | C376 | C377 | C378 | C379 | C380 | C381 | C382 | C383 | C384 | C385 | C386 | C387 | C388 | C389 | C390 | C391 | C392 | C393 | C394 | C395 | C396 | C397 | C398 | C399 | C400 | C401 | C402 | C403 | C404 | C405 | C406 | C407 | C408 | C409 | C410 | C411 | C412 | C413 | C414 | C415 | C416 | C417 | C418 | C419 | C420 | C421 | C422 | C423 | C424 | C425 | C426 | C427 | C428 | C429 | C430 | C431 | C432 | C433 | C434 | C435 | C436 | C437 | C438 | C439 | C440 | C441 | C442 | C443 | C444 | C445 | C446 | C447 | C448 | C449 | C450 | C451 | C452 | C453 | C454 | C455 | C456 | C457 | C458 | C459 | C460 | C461 | C462 | C463 | C464 | C465 | C466 | C467 | C468 | C469 | C470 | C471 | C472 | C473 | C474 | C475 | C476 | C477 | C478 | C479 | C480 | C481 | C482 | C483 | C484 | C485 | C486 | C487 | C488 | C489 | C490 | C491 | C492 | C493 | C494 | C495 | C496 | C497 | C498 | C499 | C500 | C501 | C502 | C503 | C504 | C505 | C506 | C507 | C508 | C509 | C510 | C511 | C512 | C513 | C514 | C515 | C516 | C517 | C518 | C519 | C520 | C521 | C522 | C523 | C524 | C525 | C526 | C527 | C528 | C529 | C530 | C531 | C532 | C533 | C534 | C535 | C536 | C537 | C538 | C539 | C540 | C541 | C542 | C543 | C544 | C545 | C546 | C547 | C548 | C549 | C550 | C551 | C552 | C553 | C554 | C555 | C556 | C557 | C558 | C559 | C560 | C561 | C562 | C563 | C564 | C565 | C566 | C567 | C568 | C569 | C570 | C571 | C572 | C573 | C574 | C575 | C576 | C577 | C578 | C579 | C580 | C581 | C582 | C583 | C584 | C585 | C586 | C587 | C588 | C589 | C590 | C591 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| nan | 0 | 1 | 10 | 100 | 101 | 102 | 103 | 104 | 105 | 106 | 107 | 108 | 109 | 11 | 110 | 111 | 112 | 113 | 114 | 115 | 116 | 117 | 118 | 119 | 12 | 120 | 121 | 122 | 123 | 124 | 125 | 126 | 127 | 128 | 129 | 13 | 130 | 131 | 132 | 133 | 134 | 135 | 136 | 137 | 138 | 139 | 14 | 140 | 141 | 142 | 143 | 144 | 145 | 146 | 147 | 148 | 149 | 15 | 150 | 151 | 152 | 153 | 154 | 155 | 156 | 157 | 158 | 159 | 16 | 160 | 161 | 162 | 163 | 164 | 165 | 166 | 167 | 168 | 169 | 17 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | 179 | 18 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | 187 | 188 | 189 | 19 | 190 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | 2 | 20 | 200 | 201 | 202 | 203 | 204 | 205 | 206 | 207 | 208 | 209 | 21 | 210 | 211 | 212 | 213 | 214 | 215 | 216 | 217 | 218 | 219 | 22 | 220 | 221 | 222 | 223 | 224 | 225 | 226 | 227 | 228 | 229 | 23 | 230 | 231 | 232 | 233 | 234 | 235 | 236 | 237 | 238 | 239 | 24 | 240 | 241 | 242 | 243 | 244 | 245 | 246 | 247 | 248 | 249 | 25 | 250 | 251 | 252 | 253 | 254 | 255 | 256 | 257 | 258 | 259 | 26 | 260 | 261 | 262 | 263 | 264 | 265 | 266 | 267 | 268 | 269 | 27 | 270 | 271 | 272 | 273 | 274 | 275 | 276 | 277 | 278 | 279 | 28 | 280 | 281 | 282 | 283 | 284 | 285 | 286 | 287 | 288 | 289 | 29 | 290 | 291 | 292 | 293 | 294 | 295 | 296 | 297 | 298 | 299 | 3 | 30 | 300 | 301 | 302 | 303 | 304 | 305 | 306 | 307 | 308 | 309 | 31 | 310 | 311 | 312 | 313 | 314 | 315 | 316 | 317 | 318 | 319 | 32 | 320 | 321 | 322 | 323 | 324 | 325 | 326 | 327 | 328 | 329 | 33 | 330 | 331 | 332 | 333 | 334 | 335 | 336 | 337 | 338 | 339 | 34 | 340 | 341 | 342 | 343 | 344 | 345 | 346 | 347 | 348 | 349 | 35 | 350 | 351 | 352 | 353 | 354 | 355 | 356 | 357 | 358 | 359 | 36 | 360 | 361 | 362 | 363 | 364 | 365 | 366 | 367 | 368 | 369 | 37 | 370 | 371 | 372 | 373 | 374 | 375 | 376 | 377 | 378 | 379 | 38 | 380 | 381 | 382 | 383 | 384 | 385 | 386 | 387 | 388 | 389 | 39 | 390 | 391 | 392 | 393 | 394 | 395 | 396 | 397 | 398 | 399 | 4 | 40 | 400 | 401 | 402 | 403 | 404 | 405 | 406 | 407 | 408 | 409 | 41 | 410 | 411 | 412 | 413 | 414 | 415 | 416 | 417 | 418 | 419 | 42 | 420 | 421 | 422 | 423 | 424 | 425 | 426 | 427 | 428 | 429 | 43 | 430 | 431 | 432 | 433 | 434 | 435 | 436 | 437 | 438 | 439 | 44 | 440 | 441 | 442 | 443 | 444 | 445 | 446 | 447 | 448 | 449 | 45 | 450 | 451 | 452 | 453 | 454 | 455 | 456 | 457 | 458 | 459 | 46 | 460 | 461 | 462 | 463 | 464 | 465 | 466 | 467 | 468 | 469 | 47 | 470 | 471 | 472 | 473 | 474 | 475 | 476 | 477 | 478 | 479 | 48 | 480 | 481 | 482 | 483 | 484 | 485 | 486 | 487 | 488 | 489 | 49 | 490 | 491 | 492 | 493 | 494 | 495 | 496 | 497 | 498 | 499 | 5 | 50 | 500 | 501 | 502 | 503 | 504 | 505 | 506 | 507 | 508 | 509 | 51 | 510 | 511 | 512 | 513 | 514 | 515 | 516 | 517 | 518 | 519 | 52 | 520 | 521 | 522 | 523 | 524 | 525 | 526 | 527 | 528 | 529 | 53 | 530 | 531 | 532 | 533 | 534 | 535 | 536 | 537 | 538 | 539 | 54 | 540 | 541 | 542 | 543 | 544 | 545 | 546 | 547 | 548 | 549 | 55 | 550 | 551 | 552 | 553 | 554 | 555 | 556 | 557 | 558 | 559 | 56 | 560 | 561 | 562 | 563 | 564 | 565 | 566 | 567 | 568 | 569 | 57 | 570 | 571 | 572 | 573 | 574 | 575 | 576 | 577 | 578 | 579 | 58 | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | 59 | 6 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 7 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 8 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 9 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 |
| -1 | 3015.16 | 2578.84 | -0.0035 | -0.0001 | -0.0001 | -0.0322 | -0.0106 | 0.0002 | -0.000766667 | 6.67e-05 | -0.0322 | -0.0253333 | 0.325767 | 0.9605 | 35.0687 | 76.9904 | 0.304233 | 0.944267 | 0 | 807.119 | 0.991533 | 58.4492 | 0.6079 | 0.963067 | 199.235 | 6.38833 | 15.84 | 3.91433 | 15.8967 | 15.83 | 1.2483 | 2.577 | 0.5873 | 2.97133 | -0.8198 | 0 | 0.7957 | 0.996633 | 2.29507 | 1000.15 | 37.3727 | 142.667 | 151.167 | 110.7 | 69.6667 | 947.019 | 6.3765 | 0.127933 | 0 | 10.6433 | 0.00483333 | 0.130067 | 0.0515 | 0.059 | 0.0181333 | 9.22863 | 0 | 405.013 | 3.96733 | 14.2203 | 0.3983 | 0.0120667 | 8.8865 | 0.33 | 0.0377333 | 0 | 0 | 1456.33 | 10.0615 | 593.333 | 8912 | 2175 | 0.132667 | 0.106333 | 0.211 | 3.03333 | 2.06667 | 0.198 | 0.443667 | 0.972567 | 0.618967 | 0.0892667 | 0.3898 | 0.674267 | 0.3898 | 0.692767 | 0.214233 | 0.773 | 0 | 0 | 189.173 | 18.7133 | 0.313 | 13.8233 | 24.3156 | 0.1807 | 5.48 | 0 | 18.32 | 52.742 | 0 | 12.4574 | 0 | 0 | 0 | 0 | 0 | 0.252 | 10.0033 | 17.7833 | 0.884667 | 18.1467 | 2173.17 | 1.40203 | 20.8633 | 10.0033 | 11.981 | 30.589 | 0.224033 | 6.41 | 0 | 20.8633 | 33.0187 | 6.94e-18 | -5404.42 | 0.0635 | 0.0502667 | 0.0642333 | 0.0945667 | 0.1163 | 0.0665 | 0.0666333 | 0.0854333 | 4.09587 | 0.0026 | 2665.67 | 2.17e-19 | 0.0557333 | 0.00553333 | 145.282 | 0.0456667 | 872.5 | 0 | 0.0147 | 0.0162333 | 0 | -3165.25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0054 | 0.0041 | 5468.83 | 0 | 0 | 0 | 0 | 0.00196667 | 0.3427 | 0.961033 | 0.012 | 0.0179333 | 0 | 1.26277 | 82.4375 | 0.000766667 | 1.9262 | 0.0505667 | 0.0229 | 0.37 | 0 | 0 | 0 | 0 | 1.97783 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0472 | 30.048 | 3.66047 | 7.23723 | 31.8759 | 47.3008 | 35.837 | 24.6492 | 309.731 | 0.05 | 0 | 3.64197 | 0.0014 | 0.0413667 | 69.9333 | 0.0142 | 0.0161333 | 0.006 | 3.18073 | 0 | 1.3185 | 4.6338 | 0.12 | 0.0041 | 3.10387 | 1.77407 | 0.0889 | 0.0133 | 0 | 3.55e-15 | 641.812 | 260.884 | 3734.27 | 1190.89 | 0.0601333 | 0.0482 | 1139.65 | 0.137633 | 0.0986667 | 0.910867 | 0.6426 | 0.0601667 | 0.146533 | 0.234933 | 0.0367333 | 0.1575 | 0.248433 | 0.1575 | 3.34943 | 0.2639 | 0.0824 | 0.3136 | 0 | 0 | 0 | 5.92163 | 0.0951 | 4.218 | 7.3219 | 84.9788 | 0.0508667 | 1.64963 | 0 | 5.37243 | 16.9374 | 0 | 0 | 0 | 0 | 0 | 8.8013 | 0 | 0.0863667 | 3.0548 | 5.7233 | 0.260367 | 5.2614 | 10.1653 | 3.0548 | 3.55767 | 9.73923 | 50.1866 | 0.0640333 | 2.077 | 0 | 6.55877 | 10.247 | 2.07593 | 1.7208 | 0 | 0.0160667 | 0.0236 | 64.0974 | 0.0292667 | 0.0419333 | 0.0369333 | 0.0336333 | 0.0355 | 0.0412667 | 1.40587 | 0.0008 | 0 | 0.0176 | 49.8134 | 0.0019 | 47.2056 | 0.0145333 | 255.635 | 0 | 0.00386667 | 0.00433333 | 0.00453333 | 0.00326667 | 0 | 66.2819 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0018 | 0.0015 | 0 | 0 | 86.4891 | 0 | 0 | 0.000633333 | 0.130533 | 0.310333 | 0.0035 | 0.00546667 | 0 | 24.6008 | 0.000233333 | 118.634 | 0.5442 | 0.0166 | 0.0077 | 0.123733 | 0 | 0 | 0 | 0 | 0 | 0 | 1.25197 | 57.96 | 0 | 0 | 0 | 0 | 0 | 0.0153 | 11.0279 | 1.1174 | 6.36583 | 4.9912 | 3.479 | 4.20013 | 3.20543 | 84.5917 | 10.3809 | 0 | 11.01 | 3.9163 | 8.76103 | 431.379 | 0 | 70 | 1.89063 | 4.63953 | 0 | 60.5094 | 3.51097 | 3.96167 | 1.24067 | 4.70713 | 2.65007 | 2.6931 | 351.527 | 26.8087 | 22.0663 | 319.372 | 44.9062 | 10.5566 | 5.3898 | 2.92633 | 4.35183 | 119.304 | 149.116 | 10.1957 | 13.1719 | 0.728033 | 1.01103 | 0.7776 | 1.05227 | 0.781767 | 1.0453 | 0.2478 | 0.651 | 0 | 135.328 | 0 | 0 | 5.32263 | 3.08243 | 10.2805 | 3.325 | 13.2722 | 3.78837 | 0 | 2.89683 | 730.362 | 28.1978 | 0 | 0 | 0 | 0 | 0 | 0 | 5.49547 | 126.674 | 5.04847 | 1.34673 | 8.441 | 16.3196 | 124.328 | 45.1413 | 43.0124 | 4.3625 | 19.3897 | 4.31037 | 0 | 3.3983 | 144.536 | 39.5768 | 0 | 298.405 | 130.854 | 130.495 | 406.814 | 156.642 | 172.678 | 356.035 | 255.266 | 1 | 52.0849 | 1.95343 | 0 | 2.33283 | 0.565633 | 7.93103 | 23.7007 | 9.13883 | 0 | 0 | 100 | 631.392 | 501.025 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 194.409 | 52.682 | 0 | 0 | 0 | 0 | 0 | 0.200133 | 0.325733 | 0.416067 | 2.6294 | 0 | 1.90857 | 1.78e-15 | 10.2001 | 0.0786667 | 3.2954 | 8.30223 | 2.376 | 5.78917 | 0 | 0 | 4.588 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.05637 | 4.81133 | 3.0032 | 9.78123 | 0.110067 | 0.00783333 | 0.00236667 | 7.10873 | 0.5267 | 269.213 | 49.204 | 0.152267 | 2864.33 | 9.88333 | 0.713333 | 0.0566 | 4.79897 | 0.270567 | 21.7362 | 2.44357 | 0.966433 | 0.969867 | 0.182967 | 0.933 | 0.0422667 | 18.872 | 261.891 | 0.646067 | 7.37667 | 0.1101 | 3.1017 | 0.0450333 | 2.83973 | 16.7939 | 0.953667 | 530.783 | 2.0849 | 8.4233 | 0.252733 | 2.9292 | 0.0788667 | 1.58687 | 12.2058 | 0.0123333 | 0.00593333 | 4.58157 | 0.00183333 | 16.02 | 0.502467 | 0.0137333 | 0.00356667 | 2.72997 | 0.0299333 | 0.0179333 | 0.00563333 | 61.5638 | -2.8591 | 98.123 | 352.632 | 10.5477 | 112.469 | 17.5706 | 22.8591 | 28.8774 | 701.485 | 1.18803 | 148.72 | 1 | 0.123533 | 613.821 | 81.0074 | 51.5421 | 153.926 | 8.67e-19 | -0.0221 | -0.0283 | 0.00313333 | -0.0311 | -0.0155667 | 1.48467 | -0.0514 | -0.0232333 | 0.0207 | 7.89067 | 0.133567 | 0 | 2.39357 | 0.9795 | 1831.08 | 0.1922 | 0.0186 | 9528.4 | 0.0121667 | 0.000766667 | -6.67e-05 | -0.0001 | 0 | 0.150133 | 0 | -0.245167 | -0.0148667 |
| -1 | 3021.29 | 2498.28 | -0.00136 | -7.33e-05 | 1.33e-05 | -0.01964 | -0.0105067 | -2.03e-20 | -0.00014 | 0.00122 | 0.02554 | -0.0253933 | 0.588053 | 0.967367 | 61.4005 | 138.477 | 0.245593 | 0.942033 | 0 | 765.275 | 0.98862 | 58.6329 | 0.602967 | 0.97074 | 200.872 | 6.28519 | 15.7713 | 4.43507 | 15.808 | 15.7487 | 1.32213 | 2.6624 | 0.72382 | 3.13767 | -1.49381 | 0 | 0.700167 | 0.99756 | 2.28117 | 1002.6 | 39.4415 | 96.3333 | 145.94 | 128.84 | 51.64 | 443.331 | 7.96411 | 0.37286 | 0 | 7.43133 | 0.00396 | 0.149687 | 0.0588733 | 0.04852 | 0.0136067 | 7.67197 | 0 | 411.18 | 6.78793 | 19.2604 | 0.631093 | 0.0096 | 7.22172 | 0.450667 | 0.0593333 | 0.00262 | 78.5133 | 613.6 | 9.79895 | 453.4 | 2025.33 | 16074.5 | 0.138733 | 0.112467 | 0.2078 | 2.92667 | 1.91333 | 0.183 | 0.523267 | 0.973567 | 0.68592 | 0.134227 | 0.324087 | 0.571833 | 0.324093 | 0.77358 | 0.233813 | 0.309267 | 0 | 0 | 191.073 | 19.1787 | 0.5074 | 9.456 | 26.3927 | 0.148193 | 6.29933 | 0 | 17.8507 | 47.8575 | 0 | 12.5118 | 0 | 0 | 0 | 0 | 0 | 0.292133 | 6.61733 | 18.7793 | 0.482267 | 9.796 | 2192.72 | 1.40671 | 18.9873 | 6.61733 | 8.54327 | 29.8331 | 0.1635 | 6.844 | 0 | 20.5967 | 62.3858 | 0 | -5392.62 | 0.0823333 | 0.0473867 | 0.0469133 | 0.0500533 | 0.0859733 | 0.09238 | 0.08624 | 0.0614333 | 3.73963 | 0.00297333 | 2605.25 | 0.00230667 | 0.06252 | 0.00687333 | 130.385 | 0.05252 | 938.833 | 0 | 0.0263333 | 0.01544 | 0 | -3994.88 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00521333 | 0.00455333 | -16.9611 | 0 | 0 | 0 | 0 | 0.00118667 | 0.788467 | 2.04787 | 0.0180267 | 0.0201467 | 1.08e-19 | 1.31147 | 94.6428 | 0.00126 | 3.13518 | 0.03386 | 0.0128867 | 0.348667 | 0 | 0 | 0 | 0 | 1.99423 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0721867 | 19.7815 | 3.89567 | 7.3042 | 25.6558 | 48.8854 | 42.1567 | 19.1546 | 148.749 | 0.155713 | 0 | 2.43425 | 0.00112 | 0.0471 | 70.2778 | 0.0175067 | 0.0127867 | 0.00455333 | 2.57543 | 0 | 2.14327 | 5.41651 | 0.188553 | 0.00313333 | 2.44256 | 2.07776 | 0.0931 | 0.0197067 | 0.00072 | 22.8882 | 278.307 | 201.318 | 910.935 | 7814.32 | 0.0604067 | 0.0511933 | 1410.02 | 0.1702 | 0.0927933 | 0.956 | 0.602613 | 0.0573867 | 0.16458 | 0.264433 | 0.0549067 | 0.13032 | 0.213727 | 0.13032 | 3.41021 | 0.307467 | 0.0935267 | 0.12302 | 0 | 0 | 0 | 5.9574 | 0.156813 | 2.80007 | 7.90446 | 85.0869 | 0.0439867 | 1.97341 | 0 | 5.45848 | 14.3536 | 0 | 0 | 0 | 0 | 0 | 8.75426 | 0 | 0.0857867 | 1.98515 | 5.75484 | 0.14028 | 2.88135 | 8.92389 | 1.98515 | 2.48699 | 9.2899 | 50.7224 | 0.0469 | 2.03532 | 0 | 6.3191 | 20.1603 | 1.65816 | 0.892733 | 1.73e-18 | 0.0228667 | 0.0208333 | 66.2661 | 0.0203733 | 0.0229667 | 0.02374 | 0.0463867 | 0.0433933 | 0.0294667 | 1.30095 | 0.00092 | 0.000606667 | 0.02034 | 49.2776 | 0.00232667 | 41.9052 | 0.01578 | 298.108 | 0 | 0.00694 | 0.00430667 | 0.00494 | 0.00349333 | 0 | 66.2122 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00172667 | 0.0015 | 0 | 0 | 86.713 | 0 | 0 | 0.00038 | 0.254973 | 0.63124 | 0.00503333 | 0.00687333 | 0 | 30.3021 | 0.000413333 | 118.523 | 0.934953 | 0.0119667 | 0.00428667 | 0.114073 | 0 | 0 | 0 | 0 | 0 | 0 | 1.41785 | 71.3445 | 0 | 0 | 0 | 0 | 0 | 0.0242533 | 6.81929 | 1.26753 | 4.43515 | 4.82898 | 3.10647 | 5.15792 | 2.34841 | 32.3125 | 18.3914 | 0 | 7.44761 | 3.25073 | 9.96459 | 445.926 | 206.915 | 70 | 1.40965 | 3.82317 | 0 | 93.6807 | 4.78217 | 6.42908 | 0.987013 | 3.78455 | 3.59718 | 4.23647 | 354.169 | 11.1795 | 17.3676 | 50.1622 | 317.974 | 10.5845 | 5.64011 | 2.84636 | 4.16339 | 118.992 | 120.783 | 10.0122 | 15.3583 | 0.806347 | 1.52669 | 0.639667 | 0.879313 | 0.657073 | 1.16837 | 0.26966 | 0.26112 | 0 | 135.95 | 0 | 0 | 5.41643 | 5.08463 | 6.94911 | 3.61867 | 12.0995 | 4.53361 | 0 | 2.83959 | 730.686 | 29.6416 | 0 | 0 | 0 | 0 | 0 | 0 | 6.38433 | 351.55 | 5.30609 | 1.23922 | 4.63437 | 8.42039 | 144.306 | 34.4408 | 34.3147 | 4.23583 | 16.9703 | 4.67363 | -2.78e-17 | 3.34083 | 139.537 | 57.9412 | 0 | 402.367 | 262.786 | 178.607 | 212.984 | 241.069 | 268.908 | 369.34 | 297.132 | 1 | 51.1596 | 2.28163 | 2.05872 | 2.60575 | 0.707467 | 7.24349 | 26.5887 | 10.3791 | 0 | 353.181 | 100 | 629.657 | 238.591 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 170.849 | 51.9859 | 379.523 | 0 | 0 | 0 | 0 | 0.121913 | 0.771213 | 0.886547 | 3.94345 | 0 | 2.14046 | 0 | 12.3957 | 0.126793 | 5.35035 | 5.61513 | 1.33291 | 5.55369 | 0 | 0 | 4.55433 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3.15271 | 4.80627 | 1.97331 | 9.87755 | 0.10392 | 0.00834667 | 0.00222 | 7.51323 | 0.861587 | 377.416 | 70.3355 | 0.42594 | 2846.4 | 16.1773 | 1.108 | 0.181913 | 7.20052 | 0.439633 | 45.5383 | 3.99927 | 1.46835 | 1.02592 | 0.322013 | 0.92604 | 0.0777933 | 30.1641 | 228.687 | 0.59968 | 5.93733 | 0.147153 | 2.48123 | 0.06226 | 2.25179 | 20.5933 | 0.94748 | 531.908 | 2.05567 | 8.99533 | 0.313013 | 3.09412 | 0.0922 | 1.69184 | 15.433 | 0.0175267 | 0.00729333 | 4.55635 | 0.00238667 | 15.7284 | 0.499387 | 0.0159467 | 0.00385333 | 3.19041 | 0.03134 | 0.0160333 | 0.00535333 | 66.2327 | 0.48564 | 99.8525 | 353.414 | 10.4238 | 116.436 | 13.6968 | 19.5144 | 25.6405 | 705.046 | 0.97986 | 146.439 | 1 | 0.12188 | 616.289 | 114.694 | 49.8112 | 155.243 | 8.67e-19 | 0.00219333 | -0.0271867 | -0.00496667 | 0.0271467 | -0.00545333 | 1.49611 | -0.01872 | -0.02388 | 0.00898667 | 7.37935 | 0.131247 | 0.0299333 | 2.40217 | 0.97954 | 1801.78 | 0.192847 | -0.00208667 | 9020.84 | 0.0431267 | 0.000133333 | -0.00121333 | -1.33e-05 | -6.67e-06 | 0.04126 | 0 | -0.04002 | 5.33e-05 |
| -1 | 2909.49 | 2482 | 0.00136897 | -9.31e-05 | 7.24e-05 | 0.0133241 | -0.0097931 | 8.28e-05 | -0.000117241 | 0.000917241 | -0.0235448 | -0.0265414 | 0.270286 | 0.966472 | 27.9976 | 63.7282 | 0.30271 | 0.945552 | 1.03e-05 | 740.309 | 0.985186 | 58.2116 | 0.579207 | 0.971186 | 199.793 | 6.3187 | 15.8062 | 3.718 | 15.8403 | 15.7886 | 1.13041 | 2.85114 | 0.636597 | 3.2669 | -0.560731 | 0 | 0.764741 | 0.997803 | 2.33068 | 1003.57 | 39.9818 | 131.103 | 137.493 | 123.907 | 55.3103 | 357.247 | 9.39265 | 0.38269 | 0 | 6.00207 | 0.0046069 | 0.105666 | 0.0708517 | 0.0577586 | 0.014431 | 8.13547 | 0 | 409.461 | 8.34755 | 12.8319 | 0.52751 | 0.0109448 | 7.69384 | 0.315172 | 0.0534586 | 0.00977586 | 141.555 | 1102.07 | 9.79621 | 605.966 | 1289.07 | 1794.55 | 0.122655 | 0.0786897 | 0.170276 | 2.81034 | 1.26897 | 0.134759 | 0.483379 | 0.971831 | 0.724341 | 0.112662 | 0.311221 | 0.561262 | 0.311224 | 0.809114 | 0.222738 | 0.511345 | 0 | 0 | 189.996 | 19.0779 | 0.534793 | 10.5314 | 25.0048 | 0.136814 | 6.18897 | 0 | 17.4928 | 40.5654 | 0 | 11.6535 | 0 | 0 | 0 | 0 | 0 | 0.256966 | 7.89828 | 18.611 | 0.543 | 10.3017 | 2209.41 | 1.40784 | 17.009 | 7.89828 | 9.79728 | 28.7009 | 0.144676 | 7.25759 | 0 | 18.9666 | 71.2507 | 0 | -5497.69 | 0.0774552 | 0.0514172 | 0.0493759 | 0.0513448 | 0.0701138 | 0.0814069 | 0.0788793 | 0.0597034 | 3.8208 | 0.00306897 | 2689.77 | 0.00218965 | 0.0563621 | 0.00405517 | 113.023 | 0.0487034 | 1000.73 | 0 | 0.0185655 | 0.0163862 | 0 | -3889.89 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0046931 | 0.00478276 | -1614.58 | 0 | 0 | 0 | 0 | 0.000544828 | 0.255103 | 0.968648 | 0.0555241 | 0.0222655 | 0.000117241 | 1.2868 | 105.917 | 0.00315862 | 2.75242 | 0.0308828 | 0.0143448 | 0.424379 | 0 | 0 | 0 | 0 | 1.99614 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0679828 | 20.593 | 3.76522 | 7.29701 | 31.8563 | 45.7568 | 41.7404 | 19.3621 | 115.244 | 0.131576 | 0 | 2.01625 | 0.00122414 | 0.0350103 | 69.6284 | 0.0201414 | 0.0160552 | 0.00477931 | 2.64706 | 0 | 2.53927 | 3.83293 | 0.156748 | 0.0035931 | 2.52931 | 2.35671 | 0.0832172 | 0.0186241 | 0.00312759 | 43.807 | 492.938 | 272.412 | 603.244 | 856.245 | 0.0553207 | 0.0358862 | 1537.65 | 0.192507 | 0.0769862 | 0.912417 | 0.421721 | 0.044631 | 0.161959 | 0.273514 | 0.0463103 | 0.126621 | 0.210431 | 0.126621 | 3.40372 | 0.316203 | 0.0889862 | 0.206086 | 0 | 0 | 0 | 5.99119 | 0.162038 | 3.11707 | 7.4793 | 85.5931 | 0.0421 | 1.92657 | 0 | 5.22681 | 12.1775 | 0 | 0 | 0 | 0 | 0 | 8.92859 | 0 | 0.0788379 | 2.3676 | 5.85598 | 0.158834 | 2.99925 | 8.92985 | 2.3676 | 2.89766 | 9.01618 | 50.6327 | 0.0426138 | 2.31518 | 0 | 5.83641 | 22.0906 | 2.67821 | 1.79114 | 0 | 0.0211517 | 0.0234483 | 64.5372 | 0.0224931 | 0.0231966 | 0.0197414 | 0.0399793 | 0.0398793 | 0.0292172 | 1.30309 | 0.000965517 | 0.00057931 | 0.018569 | 49.3673 | 0.00124483 | 36.0867 | 0.0153655 | 319.496 | 0 | 0.00513103 | 0.00458965 | 0.00349655 | 0.0029931 | 0 | 66.2483 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00154828 | 0.00163793 | 0 | 0 | 86.837 | 0 | 0 | 0.000168966 | 0.0822069 | 0.290497 | 0.0114483 | 0.00738276 | 3.79e-05 | 33.5761 | 0.00097931 | 118.737 | 0.833379 | 0.0100966 | 0.00455862 | 0.139907 | 0 | 0 | 0 | 0 | 0 | 0 | 1.38905 | 71.1626 | 0 | 0 | 0 | 0 | 0 | 0.0231448 | 7.13442 | 1.21674 | 5.90541 | 4.56496 | 3.1058 | 5.01796 | 2.50326 | 24.4257 | 27.5553 | 0 | 5.95803 | 3.75003 | 7.29283 | 267.352 | 159.529 | 70 | 1.49787 | 4.07065 | 0 | 92.0947 | 3.13952 | 5.46271 | 1.12965 | 4.04847 | 2.51929 | 3.8018 | 355.447 | 20.3348 | 21.5908 | 33.0946 | 142.994 | 9.52034 | 3.94049 | 2.32917 | 4.04124 | 55.1829 | 71.9225 | 10.0479 | 14.2085 | 0.846772 | 1.27864 | 0.615693 | 0.872897 | 0.630148 | 1.22148 | 0.256679 | 0.427941 | 0 | 136.446 | 0 | 0 | 5.36923 | 5.33678 | 7.71244 | 3.41412 | 11.7949 | 4.41601 | 0 | 2.77029 | 733.111 | 28.0886 | 0 | 0 | 0 | 0 | 0 | 0 | 5.53924 | 195.614 | 5.24389 | 1.1759 | 5.22872 | 8.85238 | 133.704 | 38.5871 | 36.4363 | 4.06882 | 14.9444 | 4.92547 | 0 | 3.06757 | 140.163 | 68.1185 | 0 | 302.251 | 184.235 | 218.722 | 202.69 | 258.156 | 251.631 | 345.873 | 284.622 | 1 | 51.3717 | 2.29374 | 1.94715 | 2.36338 | 0.414921 | 6.25931 | 26.3185 | 11.4982 | 0 | 227.584 | 100 | 632.056 | 199.935 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 158.872 | 61.5147 | 147.326 | 0 | 0 | 0 | 0 | 0.0551448 | 0.2513 | 0.419348 | 12.0467 | 0 | 2.36038 | 34.4828 | 14.394 | 0.327345 | 4.74746 | 5.14504 | 1.4837 | 6.71833 | 0 | 0 | 4.59883 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.90579 | 4.84472 | 2.05138 | 9.44686 | 0.111172 | 0.00866207 | 0.00251724 | 7.78598 | 0.790452 | 347.057 | 66.1548 | 0.476631 | 2857.38 | 14.2231 | 0.982414 | 0.198948 | 6.38996 | 0.404693 | 48.8254 | 3.53164 | 1.2718 | 1.02147 | 0.43081 | 0.929431 | 0.0997069 | 41.8684 | 242.643 | 0.690841 | 6.16103 | 0.165876 | 2.54392 | 0.0674759 | 2.36237 | 22.4326 | 0.949241 | 532.896 | 2.15254 | 8.9869 | 0.30791 | 3.08678 | 0.0966138 | 1.68621 | 14.2958 | 0.00823448 | 0.00502414 | 4.63124 | 0.00158965 | 26.7486 | 0.498166 | 0.0301379 | 0.00708276 | 6.18302 | 0.0240931 | 0.0146931 | 0.00465172 | 79.3479 | 2.69188 | 100.555 | 354.946 | 10.4445 | 115.689 | 14.2411 | 20.7564 | 27.6004 | 705.511 | 0.993172 | 147.718 | 1 | 0.122821 | 618.353 | 110.546 | 79.5486 | 240.792 | 0 | -0.00597931 | -0.0268586 | -0.00501035 | -0.00751379 | 0.00374138 | 1.44912 | -0.0125276 | -0.0216897 | -0.00387931 | 7.49396 | 0.134176 | 0.0271793 | 2.39289 | 0.983328 | 1810.37 | 0.18571 | -0.00535172 | 8743.49 | -0.00962069 | 0.000110345 | -0.000965517 | -1.03e-05 | 5.17e-05 | -0.0168759 | 0 | 0.0617621 | -0.00538276 |
| -1 | 2996.57 | 2463.24 | 0.00397778 | -6.67e-05 | 1.11e-05 | -0.0354667 | -0.0101778 | -6.67e-05 | -0.000533333 | 0.000866667 | 0.021 | -0.0106444 | 0.326011 | 0.9592 | 33.7687 | 77.0582 | 0.310411 | 0.954878 | -1.36e-20 | 750.672 | 0.988022 | 58.042 | 0.599511 | 0.969422 | 197.673 | 6.31226 | 15.8022 | 4.59 | 15.8644 | 15.8222 | 1.42862 | 2.66044 | 0.733978 | 3.11378 | -0.661289 | 0 | 0.710778 | 0.9962 | 2.29317 | 1005.11 | 40.1508 | 111.333 | 101.767 | 86.3222 | 58.8112 | 468.068 | 9.07824 | 0.263 | 0 | 6.39889 | 0.0041 | 0.116556 | 0.0613111 | 0.0437556 | 0.021 | 8.21179 | 0 | 412.52 | 6.92989 | 9.22222 | 0.488211 | 0.0135333 | 7.76031 | 0.388889 | 0.0435556 | 0.00643333 | 116.6 | 684.333 | 9.9339 | 412.889 | 8693.67 | 7896.67 | 0.127556 | 0.101444 | 0.181111 | 2.44444 | 1.63333 | 0.138444 | 0.489333 | 0.969933 | 0.685878 | 0.0731889 | 0.330489 | 0.597322 | 0.330511 | 0.775456 | 0.226689 | 0.430889 | 0 | 0 | 187.739 | 19.6244 | 0.598889 | 11.2956 | 30.2518 | 0.149733 | 7.96111 | 0 | 18.73 | 53.197 | 0 | 12.4537 | 0 | 0 | 0 | 0 | 0 | 0.238889 | 6.34444 | 19.5444 | 0.521111 | 10.65 | 2199.97 | 1.40279 | 17.89 | 6.34444 | 8.18444 | 31.1067 | 0.142889 | 7.78667 | 0 | 20.0067 | 60.8994 | 6.94e-18 | -5517.11 | 0.0857778 | 0.0523333 | 0.0521889 | 0.0570222 | 0.0782444 | 0.0804667 | 0.0853222 | 0.0485556 | 3.67159 | 0.00281111 | 2674.31 | 0.000722222 | 0.0563111 | 0.00296667 | 118.562 | 0.0351111 | 1094.98 | 0 | 0.0192556 | 0.0184889 | 0 | -3690.94 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0048 | 0.00496667 | -4473.8 | 0 | 0 | 0 | 0 | 0.00102222 | 0.2916 | 1.42658 | 0.0211667 | 0.0172444 | 0 | 1.28577 | 117.714 | 0.00131111 | 2.28443 | 0.0316778 | 0.0151444 | 0.442433 | 0 | 0 | 0 | 0 | 1.99591 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0544556 | 21.8749 | 3.90039 | 7.27614 | 27.9804 | 33.997 | 28.5237 | 21.0699 | 149.38 | 0.0899111 | 0 | 2.1588 | 0.00113333 | 0.0386222 | 69.4704 | 0.0174889 | 0.0122556 | 0.00692222 | 2.68047 | 0 | 2.29129 | 2.7456 | 0.143233 | 0.00451111 | 2.56478 | 2.3284 | 0.0926444 | 0.0141333 | 0.00195556 | 34.2591 | 309.893 | 181.742 | 4102.92 | 3747.97 | 0.0560111 | 0.0440444 | 1275.85 | 0.1891 | 0.0781333 | 0.788311 | 0.501978 | 0.0451444 | 0.160544 | 0.263533 | 0.0299 | 0.132889 | 0.223733 | 0.132889 | 3.37963 | 0.308011 | 0.0899889 | 0.181856 | 0 | 0 | 0 | 6.07591 | 0.179867 | 3.22909 | 8.97727 | 85.0789 | 0.0442111 | 2.49416 | 0 | 5.72779 | 17.3337 | 0 | 0 | 0 | 0 | 0 | 8.70207 | 0 | 0.0782111 | 1.79362 | 6.0117 | 0.153522 | 3.12078 | 9.37921 | 1.79362 | 2.40161 | 9.47783 | 50.4183 | 0.0421667 | 2.34536 | -5.42e-20 | 5.9627 | 19.5332 | 2.12837 | 1.56953 | 0 | 0.0247111 | 0.0242444 | 64.2819 | 0.0234778 | 0.0265222 | 0.0244556 | 0.0420222 | 0.0425889 | 0.0232667 | 1.2543 | 0.000866667 | 0.000222222 | 0.0189778 | 49.5817 | 0.000977778 | 39.5951 | 0.0114556 | 357.292 | 0 | 0.00504444 | 0.00507778 | 0.0029 | 0.00275556 | 0 | 66.2044 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00164444 | 0.00168889 | 0 | 0 | 87.023 | 0 | 0 | 0.000333333 | 0.0917778 | 0.455367 | 0.00508889 | 0.00541111 | 0 | 36.9309 | 0.000433333 | 118.426 | 0.707689 | 0.0107222 | 0.00513333 | 0.144056 | 0 | 0 | 0 | 0 | 0 | 0 | 1.36406 | 69.8422 | 0 | 0 | 0 | 0 | 0 | 0.0178444 | 7.71034 | 1.23607 | 5.07929 | 3.39548 | 2.63178 | 3.54281 | 2.66784 | 38.713 | 19.8622 | 0 | 6.29752 | 3.37102 | 7.7066 | 381.45 | 216.419 | 70 | 2.20309 | 4.156 | 0 | 75.0811 | 2.2426 | 4.89981 | 1.40193 | 4.13631 | 3.12193 | 3.10826 | 356.01 | 12.4663 | 15.3694 | 314.676 | 200.085 | 9.9121 | 5.08511 | 2.48849 | 3.56453 | 71.6278 | 77.5177 | 10.0609 | 14.4609 | 0.805778 | 0.844556 | 0.655467 | 0.929111 | 0.666656 | 1.17131 | 0.260689 | 0.363778 | 0 | 135.14 | 0 | 0 | 5.50863 | 5.96229 | 8.36574 | 4.12636 | 12.6628 | 5.72237 | 0 | 2.96467 | 732.266 | 34.1006 | 0 | 0 | 0 | 0 | 0 | 0 | 5.21317 | 313.316 | 5.5045 | 1.22993 | 4.99108 | 9.17862 | 136.438 | 33.1832 | 32.2777 | 4.40133 | 14.4172 | 5.2858 | 2.78e-17 | 3.23511 | 140.059 | 62.2222 | 0 | 271.425 | 173.787 | 237.936 | 167.581 | 328.968 | 175.209 | 435.347 | 265.231 | 1 | 53.4007 | 2.16538 | 0.633644 | 2.35591 | 0.305611 | 6.65437 | 20.0366 | 12.1669 | 0 | 314.656 | 100 | 631.209 | 210.194 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 162.456 | 51.6072 | 104.984 | 0 | 0 | 0 | 0 | 0.104733 | 0.287578 | 0.617467 | 4.5009 | 0 | 1.80842 | 0 | 15.7338 | 0.134544 | 3.92067 | 5.29686 | 1.56698 | 7.0058 | 0 | 0 | 4.59644 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.37511 | 4.85122 | 2.17877 | 9.70949 | 0.110089 | 0.00803333 | 0.00242222 | 7.30231 | 0.622256 | 222.608 | 41.9309 | 0.233222 | 2859.11 | 8.75556 | 0.601111 | 0.0912 | 4.04977 | 0.238344 | 21.7264 | 2.18674 | 0.791667 | 0.994156 | 0.3111 | 0.928778 | 0.0730778 | 30.1794 | 180.098 | 0.432067 | 3.78222 | 0.0872 | 1.48851 | 0.0349444 | 1.40676 | 13.7704 | 0.9475 | 531.442 | 2.06561 | 56.5955 | 0.369589 | 19.3355 | 0.117511 | 10.7729 | 18.1905 | 0.00775556 | 0.00536667 | 4.57922 | 0.00185556 | 15.8387 | 0.499767 | 0.0143444 | 0.00363333 | 2.86918 | 0.0239 | 0.0188444 | 0.00625556 | 62.457 | 2.50091 | 101.717 | 355.073 | 10.4841 | 115.419 | 13.6783 | 19.7213 | 26.2256 | 706.041 | 0.998956 | 147.475 | 1 | 0.121889 | 617.967 | 98.5603 | 68.3177 | 207.423 | 0 | -0.0133 | -0.0230222 | -0.00134444 | -0.0231 | 0.0132778 | 1.49511 | -0.0129444 | -0.0183444 | 0.0181889 | 6.98559 | 0.130022 | 0.0126444 | 2.3934 | 0.982789 | 1787.61 | 0.177789 | -0.00395556 | 8967.24 | 0.0299556 | 0.000511111 | -0.000855556 | -3.39e-21 | 1.11e-05 | 0.0159889 | 0 | 0.0254444 | 0.00494444 |
| -1 | 3056.64 | 2496.24 | -0.004175 | -3.39e-21 | 2.54e-21 | -0.054925 | -0.01105 | 0.00025 | -0.00105 | -0.001275 | 0.0349 | -0.004025 | 0.97835 | 0.9685 | 101.256 | 231.896 | 0.3488 | 0.938975 | 0 | 763.501 | 0.984825 | 57.6116 | 0.603175 | 0.96735 | 199.518 | 6.2941 | 15.8625 | 4.56725 | 15.8825 | 15.86 | 1.4346 | 2.689 | 0.7508 | 3.233 | -0.776825 | 0 | 0.719275 | 0.998525 | 2.2991 | 1006.53 | 39.5986 | 125.5 | 136.325 | 136.475 | 55.25 | 322.175 | 10.5306 | 0.199175 | 0 | 5.92 | 0.0035 | 0.111375 | 0.063425 | 0.05535 | 0.0114 | 10.7139 | 0 | 422.316 | 7.60725 | 10.649 | 0.469375 | 0.0069 | 10.2702 | 0.2125 | 0.05415 | 0 | 0 | 546.25 | 9.79803 | 415.5 | 3452.25 | 35938.8 | 0.121 | 0.14475 | 0.25525 | 2.9 | 1.325 | 0.133 | 0.3825 | 0.97845 | 0.693625 | 0.08905 | 0.3314 | 0.637525 | 0.3314 | 0.745125 | 0.254975 | 0.262 | 0 | 0 | 189.72 | 17.98 | 0.577 | 7.325 | 24.3828 | 0.206675 | 8.6675 | 0 | 18.51 | 29.5648 | 0 | 12.5322 | 0 | 0 | 0 | 0 | 0 | 0.25025 | 7.1725 | 21.0825 | 0.36825 | 5.9775 | 2219.52 | 1.40993 | 20.11 | 7.1725 | 8.675 | 28.9123 | 0.119075 | 6.7675 | 0 | 21.9925 | 63.4765 | 0 | -5431.5 | 0.11035 | 0.04445 | 0.04505 | 0.03225 | 0.151875 | 0.09595 | 0.075575 | 0.074025 | 2.94433 | 0.0031 | 2629.81 | 0.006125 | 0.050825 | 0.002925 | 167.555 | 0.040825 | 1593.8 | 0 | 0.01545 | 0.01525 | 0 | -4005.44 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00405 | 0.0044 | -389.521 | 0 | 0 | 0 | 0 | 0.002525 | 0.9291 | 2.52908 | 0.019375 | 0.020925 | 0 | 1.29228 | 142.718 | 0.001325 | 2.61232 | 0.0259 | 0.014825 | 0.230725 | 0 | 0 | 0 | 0 | 1.98705 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.075725 | 19.1025 | 3.97375 | 7.272 | 31.5206 | 45.1267 | 48.9962 | 19.9378 | 104.032 | 0.062625 | 0 | 1.9057 | 0.000925 | 0.03945 | 73.4611 | 0.019925 | 0.0143 | 0.00385 | 3.38998 | 0 | 2.42742 | 3.34145 | 0.1375 | 0.0023 | 3.2728 | 1.76665 | 0.05605 | 0.020375 | 0 | 0 | 245.632 | 190.991 | 1647.45 | 17033.6 | 0.057425 | 0.061625 | 1391.06 | 0.137 | 0.114375 | 1.01625 | 0.409 | 0.042025 | 0.128025 | 0.274 | 0.03655 | 0.1416 | 0.235725 | 0.1416 | 3.36335 | 0.289225 | 0.097825 | 0.108475 | 0 | 0 | 0 | 6.01393 | 0.167625 | 2.14405 | 7.48 | 84.9514 | 0.065075 | 2.7033 | 0 | 5.64273 | 8.95455 | 0 | 0 | 0 | 0 | 0 | 8.42625 | 0 | 0.0834 | 2.10495 | 6.27845 | 0.111175 | 1.89047 | 8.95617 | 2.10495 | 2.5359 | 9.22743 | 50.3426 | 0.035125 | 2.01195 | 0 | 6.56658 | 20.3419 | 1.13745 | 0.71005 | 0 | 0.030225 | 0.01975 | 64.3162 | 0.020425 | 0.014575 | 0.0389 | 0.0471 | 0.038125 | 0.0365 | 1.04035 | 0.000925 | 0.00165 | 0.016775 | 49.6574 | 0.000875 | 54.1479 | 0.012775 | 514.887 | 0 | 0.0041 | 0.004325 | 0.00365 | 0.0028 | 0 | 66.1556 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00145 | 0.001525 | 0 | 0 | 86.9332 | 0 | 0 | 0.00085 | 0.290225 | 0.764975 | 0.005175 | 0.0067 | 0 | 46.9937 | 0.000425 | 117.994 | 0.81795 | 0.009375 | 0.0048 | 0.08035 | 0 | 0 | 0 | 0 | 0 | 0 | 1.17643 | 79.77 | 0 | 0 | 0 | 0 | 0 | 0.027075 | 6.3669 | 1.47715 | 5.69398 | 4.44567 | 2.8065 | 5.5045 | 2.48807 | 24.1156 | 16.5766 | 0 | 5.9916 | 2.87498 | 7.72535 | 581.308 | 660.722 | 70 | 1.18332 | 5.3746 | 0 | 74.4094 | 2.52925 | 4.79823 | 0.70455 | 5.4188 | 1.6954 | 3.84028 | 352.377 | 10.0777 | 15.8814 | 93.3735 | 0 | 9.3463 | 7.2805 | 3.5181 | 3.9693 | 79.0644 | 104.93 | 10.1147 | 11.4215 | 0.8177 | 1.06157 | 0.658075 | 0.99125 | 0.667625 | 1.1264 | 0.293325 | 0.222025 | 0 | 131.904 | 0 | 0 | 5.10497 | 5.71457 | 5.5013 | 3.37697 | 18.2233 | 6.32988 | 0 | 2.97907 | 722.949 | 47.2745 | 0 | 0 | 0 | 0 | 0 | 0 | 5.39628 | 346.165 | 5.96342 | 1.0932 | 3.53558 | 5.3145 | 182.189 | 37.8409 | 36.272 | 4.1421 | 12.3077 | 4.67873 | 0 | 3.60175 | 137.488 | 60.8235 | 0 | 200.035 | 86.7635 | 119.584 | 39.5652 | 505.821 | 484.767 | 236.925 | 122.653 | 1 | 39.819 | 2.38535 | 5.28587 | 2.09357 | 0.299725 | 9.2107 | 20.6939 | 17.6257 | 0 | 108.017 | 100 | 621.768 | 307.58 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 72.4203 | 38.017 | 513.655 | 0 | 0 | 0 | 0 | 0.2624 | 0.918125 | 1.09238 | 4.15658 | 0 | 2.23445 | 0 | 18.5071 | 0.138475 | 4.5438 | 4.29277 | 1.53855 | 3.64075 | 0 | 0 | 4.60275 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3.2588 | 4.846 | 1.89522 | 10.1565 | 0.11395 | 0.009 | 0.00235 | 7.91082 | 0.78745 | 303.158 | 55.651 | 0.464 | 2847.5 | 12.3925 | 1.13 | 0.216025 | 5.59638 | 0.4713 | 40.2119 | 3.06515 | 1.5168 | 0.958825 | 0.263575 | 0.931875 | 0.050225 | 27.4422 | 253.588 | 0.7974 | 5.82 | 0.20965 | 2.32 | 0.090175 | 2.30575 | 26.3665 | 0.9498 | 532.917 | 2.12412 | 8.155 | 0.31195 | 2.64432 | 0.094425 | 1.53055 | 14.6745 | 0 | 0 | 4.6423 | 0 | 0 | 0.5007 | 0.01335 | 0.00375 | 2.66613 | 0.02425 | 0.01575 | 0.005525 | 67.6365 | 0.52295 | 98.057 | 353.494 | 10.4752 | 112.427 | 11.1757 | 19.477 | 24.4341 | 698.515 | 0.95945 | 145.262 | 1 | 0.121775 | 611.182 | 105.004 | 39.0728 | 116.909 | 0 | 0.008975 | -0.0233 | 0.031625 | 0.01415 | 0.005475 | 1.4604 | -0.005525 | -0.003375 | 0.000175 | 7.55037 | 0.129725 | 0.0866 | 2.42565 | 0.9859 | 1819.54 | 0.19735 | -0.0037 | 8931.33 | 0.0438 | 0.00105 | 0.001275 | -2.5e-05 | 0 | 0.020025 | 0 | -0.028275 | -0.02 |
| -1 | 2966.59 | 2500.81 | -0.0101 | -3.39e-21 | -0.000133333 | -0.00173333 | -0.0111667 | -0.000566667 | -0.00146667 | -0.000633333 | -0.0147667 | -0.0243 | 0.653467 | 0.959967 | 67.8869 | 153.237 | 0.308633 | 0.946733 | 0 | 761.216 | 0.990433 | 59.2604 | 0.5999 | 0.973433 | 202.967 | 6.22273 | 15.76 | 3.39167 | 15.7933 | 15.7167 | 0.917633 | 2.90267 | 0.589533 | 3.34967 | -1.05567 | 0 | 0.811 | 0.998067 | 2.30883 | 1004.31 | 38.4013 | 100.667 | 102.633 | 79.3667 | 62.0667 | 410.275 | 8.1714 | 0.174567 | 0 | 6.54667 | 0.0045 | 0.0923667 | 0.0635 | 0.0593667 | 0.0364 | 9.67597 | 0 | 415.537 | 5.93567 | 12.961 | 0.837967 | 0.0269667 | 8.8889 | 0.316667 | 0.0566 | 0 | 0 | 849.667 | 9.47987 | 291.333 | 10466.3 | 18802.3 | 0.098 | 0.106333 | 0.200333 | 2.73333 | 1.86667 | 0.172 | 0.415667 | 0.969 | 0.497033 | 0.0914 | 0.318867 | 0.6147 | 0.318867 | 0.689333 | 0.2236 | 0.571 | 0 | 0 | 193.487 | 17.4433 | 0.500333 | 11.6867 | 29.069 | 0.132433 | 5.63 | 0 | 20.4733 | 50.7033 | 0 | 12.5715 | 0 | 0 | 0 | 0 | 0 | 0.207667 | 8.69333 | 21.21 | 0.475667 | 9.03667 | 2204.79 | 1.41183 | 19.0767 | 8.69333 | 11.1713 | 29.9653 | 0.218333 | 9.57667 | 0 | 21.0433 | 52.6927 | 6.94e-18 | -5385.67 | 0.0687667 | 0.0666 | 0.039 | 0.0455667 | 0.0636333 | 0.0727667 | 0.0896333 | 0.0776333 | 4.78537 | 0.00513333 | 2563.25 | 0.0026 | 0.0629333 | 0.00136667 | 110.772 | 0.0886 | 1109.87 | 0 | 0.018 | 0.0218667 | 0 | -2026.67 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00406667 | 0.0044 | 1871.83 | 0 | 0 | 0 | 0 | 0.00153333 | 0.559667 | 2.83623 | 0.0156 | 0.0138 | 0 | 1.32957 | 105.799 | 0.0008 | 3.62217 | 0.0287333 | 0.00973333 | 0.332233 | 0 | 0 | 0 | 0 | 2.01483 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0792 | 14.837 | 3.70833 | 7.37117 | 27.8171 | 34.1961 | 29.6298 | 21.9723 | 126.194 | 0.0634667 | 0 | 2.21083 | 0.00123333 | 0.0279333 | 67.5074 | 0.0211 | 0.0157 | 0.0109333 | 3.23763 | 0 | 1.8205 | 4.23313 | 0.238933 | 0.008 | 3.03503 | 2.17407 | 0.0802333 | 0.0197667 | 0 | 3.55e-15 | 372.176 | 128.039 | 4836.52 | 8965.7 | 0.0423 | 0.0455 | 1558.78 | 0.181067 | 0.0874 | 0.8917 | 0.5504 | 0.0585 | 0.135567 | 0.199467 | 0.0358 | 0.131933 | 0.2235 | 0.131933 | 3.4647 | 0.2727 | 0.0916 | 0.2405 | 0 | 0 | 0 | 5.5306 | 0.150567 | 3.35527 | 8.47717 | 86.3876 | 0.0385 | 1.55947 | 0 | 6.174 | 14.7951 | 0 | 0 | 0 | 0 | 0 | 8.78097 | 0 | 0.0681 | 2.4546 | 6.52283 | 0.136333 | 2.82533 | 9.88777 | 2.4546 | 3.00777 | 9.1205 | 50.4515 | 0.0602667 | 2.6874 | 0 | 6.64093 | 17.8396 | 0 | 0 | 0 | 0.0207 | 0.0301 | 63.9803 | 0.0175333 | 0.0211333 | 0.0175333 | 0.0356667 | 0.0474667 | 0.0389 | 1.83443 | 0.0015 | 0.0008 | 0.0197 | 49.5485 | 0.000466667 | 37.7733 | 0.0286333 | 373.375 | 0 | 0.0049 | 0.00533333 | 0.0042 | 0.00303333 | 0 | 66.2779 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00126667 | 0.00156667 | 0 | 0 | 86.6507 | 0 | 0 | 0.0005 | 0.1817 | 0.807467 | 0.00403333 | 0.00503333 | 0 | 35.6794 | 0.000233333 | 118.261 | 1.0566 | 0.00926667 | 0.00296667 | 0.1042 | 0 | 0 | 0 | 0 | 0 | 0 | 1.3031 | 79.4867 | 0 | 0 | 0 | 0 | 0 | 0.0275 | 5.43327 | 1.2237 | 4.6743 | 3.47337 | 3.603 | 3.1749 | 2.8177 | 25.8703 | 14.6181 | 0 | 6.80303 | 3.70487 | 6.39783 | 390.788 | 352.931 | 70 | 3.83137 | 4.7685 | 0 | 72.7674 | 3.11603 | 8.98007 | 2.81103 | 4.5973 | 2.52077 | 3.99393 | 357.181 | 15.8627 | 11.1321 | 670.654 | 175.92 | 7.3838 | 5.27233 | 2.71317 | 4.04797 | 86.4152 | 93.7786 | 10.1732 | 11.9942 | 0.576567 | 1.0419 | 0.6319 | 0.9608 | 0.643633 | 1.0401 | 0.258 | 0.4824 | 0 | 135.452 | 0 | 0 | 4.87137 | 4.92453 | 8.6379 | 3.95033 | 10.6151 | 3.97027 | 0 | 3.228 | 736.013 | 25.9693 | 0 | 0 | 0 | 0 | 0 | 0 | 4.50497 | 407.562 | 5.9336 | 1.21717 | 4.56263 | 7.82543 | 146.482 | 43.498 | 42.2119 | 4.22713 | 21.6723 | 6.428 | 0 | 3.38633 | 142.272 | 59.7289 | 0 | 409.435 | 166.037 | 143.451 | 269.052 | 456.239 | 122.304 | 351.924 | 91.5597 | 1 | 66.1391 | 3.8858 | 2.26357 | 2.6197 | 0.138 | 6.0515 | 45.6968 | 12.6695 | 0 | 239.475 | 100 | 634.905 | 275.101 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 182.58 | 35.336 | 793.582 | 0 | 0 | 0 | 0 | 0.157233 | 0.549467 | 1.2357 | 3.36673 | 0 | 1.46063 | 1.78e-15 | 13.935 | 0.0799667 | 6.114 | 4.79593 | 1.00217 | 5.38377 | 0 | 0 | 4.571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3.43073 | 4.83633 | 1.4774 | 9.5967 | 0.113067 | 0.0078 | 0.00246667 | 6.89913 | 1.0186 | 401.717 | 76.1347 | 0.531933 | 2870.33 | 16.2067 | 1.26 | 0.2153 | 7.77233 | 0.4923 | 45.3408 | 4.0325 | 1.66627 | 0.965433 | 0.3655 | 0.923167 | 0.0761333 | 37.9581 | 260.257 | 0.8063 | 4.43667 | 0.172733 | 1.8496 | 0.0701333 | 1.7118 | 21.5186 | 0.945167 | 533.279 | 1.96413 | 10.35 | 0.233667 | 3.63873 | 0.0687 | 1.94317 | 12.0155 | 0.0137667 | 0.00596667 | 4.59887 | 0.0018 | 29.8944 | 0.5002 | 0.0144 | 0.0037 | 2.87477 | 0.0247333 | 0.0078 | 0.00253333 | 35.4509 | -0.2406 | 95.9941 | 357.332 | 10.4862 | 115.212 | 13.8792 | 20.2406 | 26.6279 | 709.385 | 1.01757 | 148.883 | 1 | 0.121433 | 621.427 | 95.1847 | 0 | 0 | 8.67e-19 | -0.00636667 | -0.0582667 | -0.0346667 | -0.004 | -0.0004 | 1.44033 | -0.0603667 | -0.0255333 | 0.0016 | 7.27513 | 0.133867 | 0.0382667 | 2.4041 | 0.988633 | 1828.78 | 0.188933 | -0.0043 | 8785.58 | 0.0049 | 0.0015 | 0.000666667 | -0.000133333 | 0 | 0.140233 | 0 | -0.276867 | 0.0403 |
| -1 | 3010.72 | 2484.3 | 0.000322222 | -1.56e-05 | -1.11e-05 | 0.0216622 | -0.00843556 | 2.22e-06 | -0.00200667 | 0.000246667 | 0.00545556 | -0.00548667 | 5.55e-17 | 0.962713 | 7.11e-15 | -1.42e-14 | 0.319298 | 0.945253 | 2.89e-05 | 742.976 | 0.988878 | 58.5133 | 0.598189 | 0.967307 | 199.971 | 6.28926 | 15.8067 | 3.83787 | 15.8373 | 15.8364 | 1.13854 | 2.71293 | 0.635716 | 3.17822 | -0.13016 | 0 | 0.755751 | 0.997964 | 2.33618 | 1004.63 | 38.6671 | 117.4 | 132.204 | 129.882 | 58.3978 | 313.33 | 9.28274 | 0.290396 | 0 | 5.99933 | 0.00439778 | 0.106789 | 0.0603867 | 0.0621 | 0.0171089 | 7.51289 | 0 | 414.839 | 6.57651 | 11.7091 | 0.61406 | 0.0120511 | 7.06627 | 0.44 | 0.0515667 | 0.0049 | 73.1644 | 422.2 | 9.83531 | 619.156 | 3080.51 | 138.022 | 0.109911 | 0.0792 | 0.164378 | 2.90222 | 0.862222 | 0.0828222 | 0.161711 | 0.969924 | 0.719564 | 0.108469 | 0.309131 | 0.574462 | 0.309136 | 0.746582 | 0.254771 | 0.431733 | 0 | 0 | 190.135 | 18.3367 | 0.548267 | 10.5431 | 26.6145 | 0.137564 | 7.56178 | 0 | 17.4567 | 40.6 | 0 | 12.2138 | 0 | 0 | 0 | 0 | 0 | 0.262111 | 6.84356 | 19.6018 | 0.486022 | 9.47444 | 2202.41 | 1.40565 | 17.63 | 6.84356 | 8.24556 | 28.415 | 0.218396 | 8.78089 | 4.34e-19 | 19.5758 | 77.5622 | 6.94e-18 | -6397.9 | 0.0910733 | 0.0521378 | 0.0538289 | 0.0720511 | 0.0916089 | 0.0809489 | 0.07762 | 0.0701578 | 3.62817 | 0.00301333 | 3018.01 | 0 | 0.0614333 | 0.00803111 | 128.941 | 0.0459533 | 1018.03 | 0 | 0.0212844 | 0.0203689 | 0 | -4051.91 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00418 | 0.00431333 | 1439.71 | 0 | 0 | 0 | 0 | 4.34e-19 | 1.11e-16 | 0 | 0.0372956 | 0.0253911 | 0.000282222 | 0.984716 | 109.589 | 0.00180444 | 2.9985 | 0.0284156 | 0.0182867 | 0.466778 | 0 | 0 | 0 | 0 | 1.88806 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0613911 | 19.4691 | 3.81287 | 5.12327 | 29.4106 | 44.9069 | 43.8879 | 20.0435 | 102.328 | 0.0944644 | 0 | 1.97345 | 0.00119333 | 0.0363022 | 68.1573 | 0.0164111 | 0.0171778 | 0.00571333 | 2.51669 | 0 | 2.04679 | 3.45042 | 0.180164 | 0.00400444 | 2.40277 | 2.63828 | 0.106069 | 0.0176822 | 0.00140222 | 23.2898 | 184.421 | 271.215 | 1374.68 | 62.0725 | 0.0471289 | 0.0343556 | 1374.27 | 0.185956 | 0.0729489 | 0.932444 | 0.28318 | 0.0270533 | 0.05104 | 0.281469 | 0.0430022 | 0.122864 | 0.217809 | 0.122869 | 4.65245 | 0.290289 | 0.100893 | 0.176327 | 0 | 0 | 0 | 5.77735 | 0.174027 | 3.09701 | 7.86773 | 85.6739 | 0.0415311 | 2.32908 | 0 | 5.24781 | 12.6959 | 0 | 0 | 0 | 0 | 0 | 9.17727 | 0 | 0.07794 | 2.02228 | 6.0177 | 0.146398 | 2.79558 | 9.1134 | 2.02228 | 2.42506 | 8.69212 | 50.6973 | 0.06716 | 2.62586 | -5.42e-20 | 5.83936 | 24.5545 | 5.92023 | 4.42878 | -1.73e-18 | 0.0257711 | 0.0234689 | 64.6857 | 0.0242667 | 0.0338556 | 0.0253756 | 0.0399089 | 0.0393978 | 0.0348422 | 1.25635 | 0.00094 | 5.42e-20 | 0.0200889 | 49.3027 | 0.00254889 | 42.4295 | 0.0142 | 325.864 | 0 | 0.00576222 | 0.00536667 | 0.00440222 | 0.00325333 | 0 | 66.3106 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00139556 | 0.00155111 | 0 | 0 | 86.9432 | 0 | 0 | 0 | 0 | -1.11e-16 | 0.00774667 | 0.00833333 | 8.89e-05 | 34.6727 | 0.000566667 | 118.931 | 0.903556 | 0.00957333 | 0.00584222 | 0.156082 | 0 | 0 | 0 | 0 | 0 | 0 | 1.26931 | 62.1158 | 0 | 0 | 0 | 0 | 0 | 0.0209022 | 6.89459 | 1.22506 | 5.28262 | 4.3801 | 3.57651 | 5.24688 | 2.6526 | 23.712 | 22.7055 | 0 | 5.9256 | 3.59235 | 7.21154 | 251.145 | 293.016 | 70 | 1.79576 | 3.75234 | 0 | 72.0078 | 2.83078 | 6.25769 | 1.25544 | 3.71222 | 3.51813 | 3.66918 | 357.36 | 6.59678 | 20.527 | 79.2407 | 9.88883 | 11.1603 | 4.19353 | 3.21247 | 4.26465 | 33.8701 | 45.697 | 9.9743 | 3.4758 | 0.840387 | 1.19514 | 0.611849 | 0.891458 | 0.625858 | 1.12584 | 0.293062 | 0.362696 | 0 | 133.065 | 0 | 0 | 5.13622 | 5.50635 | 7.90177 | 3.64748 | 12.0225 | 5.41597 | 0 | 2.77068 | 729.704 | 28.8239 | 0 | 0 | 0 | 0 | 0 | 0 | 5.68566 | 208.875 | 5.50322 | 1.16294 | 4.69991 | 8.30367 | 136.318 | 37.6657 | 33.4633 | 4.03628 | 21.4487 | 5.97531 | -2.78e-17 | 3.17227 | 140.105 | 88.9763 | 0 | 315.687 | 187.975 | 310.653 | 175.169 | 287.506 | 209.424 | 361.734 | 247.314 | 1 | 49.0217 | 2.2708 | 2.22e-16 | 2.56143 | 0.825504 | 7.11598 | 25.1132 | 11.6076 | 0 | 288.47 | 100 | 630.529 | 227.035 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 151.827 | 58.4042 | 340.251 | 0 | 0 | 0 | 0 | -5.55e-17 | 0 | 1.11e-16 | 8.08867 | 0 | 2.69818 | 22.2222 | 14.8947 | 0.184889 | 5.12166 | 4.75162 | 1.90768 | 7.41506 | 0 | 0 | 4.59507 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.61899 | 4.83442 | 1.93842 | 9.84391 | 0.10986 | 0.00784 | 0.00259333 | 7.13581 | 0.730611 | 270.649 | 51.1944 | 0.81318 | 2863.09 | 11.6391 | 0.810222 | 0.338538 | 5.26052 | 0.330533 | 60.0451 | 2.86612 | 1.05173 | 0.982082 | 0.341482 | 0.930064 | 0.0669044 | 34.6149 | 196.201 | 0.557422 | 6.13133 | 0.125347 | 2.55933 | 0.0512756 | 2.36392 | 16.5819 | 0.95046 | 529.618 | 2.14795 | 20.7473 | 0.339238 | 6.73791 | 0.103084 | 4.20183 | 15.8363 | 0.00333778 | 0.00268667 | 4.60774 | 0.000926667 | 22.9549 | 0.500842 | 0.01518 | 0.00376 | 3.0302 | 0.0179067 | 0.0162156 | 0.00527111 | 114.186 | 6.81711 | 101.56 | 356.153 | 10.4389 | 114.104 | 14.4413 | 18.9607 | 25.5158 | 704.189 | 1.02439 | 146.332 | 1 | 0.122327 | 616.588 | 92.8994 | 89.877 | 280.606 | 0 | 0.000608889 | -0.0303644 | -0.00181111 | -0.0332044 | 0.0137333 | 1.47756 | -0.0268867 | -0.0240044 | 0.0138022 | 7.52398 | 0.132213 | -3.47e-18 | 2.404 | 0.981502 | 1816.89 | 0.181518 | 0.000706667 | 8814.7 | -0.00772667 | 0.00198667 | -0.000337778 | -2.89e-05 | 4.89e-05 | 0.0128867 | 0 | -0.0130444 | -0.00172222 |
| -1 | 3071.24 | 2505.61 | 0.002325 | 0.000225 | 5e-05 | -0.04335 | -0.00955 | 0.000575 | -7.5e-05 | -0.0006 | -0.009025 | -0.03235 | 0.489175 | 0.95985 | 50.6403 | 115.397 | 0.113175 | 0.947875 | 0 | 732.966 | 0.987475 | 58.4388 | 0.594375 | 0.97685 | 200.341 | 6.20678 | 15.815 | 3.342 | 15.8725 | 15.815 | 1.13573 | 2.77875 | 0.548425 | 3.1025 | -1.04008 | 0 | 0.774725 | 0.99635 | 2.2823 | 1002.61 | 39.2415 | 102.75 | 178 | 141.8 | 54.6 | 638.783 | 9.57525 | 0.444725 | 0 | 5.99 | 0.0035 | 0.130675 | 0.065875 | 0.07465 | 0.020975 | 8.92395 | 0 | 404.254 | 10.2855 | 10.982 | 0.43595 | 0.0146 | 8.5072 | 0.3 | 0.095825 | 0.0064 | 362.85 | 549.25 | 10.0115 | 567 | 2224 | 5013.25 | 0.11825 | 0.123 | 0.24675 | 2.45 | 1.4 | 0.159 | 0.51875 | 0.9687 | 0.644625 | 0.137225 | 0.3428 | 0.63465 | 0.342825 | 0.807025 | 0.1962 | 0.43475 | 0 | 0 | 190.33 | 20.395 | 0.45425 | 14.7925 | 31.4243 | 0.228725 | 9.475 | 0 | 17.3475 | 44.422 | 0 | 12.4523 | 0 | 0 | 0 | 0 | 0 | 0.31175 | 9.315 | 17.4025 | 0.84175 | 18.235 | 2206.51 | 1.3862 | 18.8025 | 9.315 | 9.96075 | 31.975 | 0.15125 | 9.3625 | 0 | 20.4975 | 83.6125 | 0 | -5620.56 | 0.089075 | 0.057175 | 0.0531 | 0.061975 | 0.094575 | 0.080275 | 0.0991 | 0.085225 | 3.77332 | 0.001675 | 2719.06 | 0.001975 | 0.061725 | 0.00425 | 108.207 | 0.066975 | 865.175 | 0 | 0.015525 | 0.015775 | 0 | -4501.44 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0051 | 0.005825 | -8605.46 | 0 | 0 | 0 | 0 | 0.00135 | 0.486775 | 1.7467 | 0.114975 | 0.0229 | 0 | 1.27507 | 83.9379 | 0.035275 | 3.54312 | 0.033625 | 0.008575 | 0.371025 | 0 | 0 | 0 | 0 | 1.9959 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.058975 | 22.2087 | 3.23013 | 7.33793 | 27.6778 | 60.3657 | 51.5966 | 18.8431 | 202.333 | 0.151975 | 0 | 1.89817 | 0.000925 | 0.045025 | 69.2306 | 0.0195 | 0.019575 | 0.007025 | 2.95412 | 0 | 3.2119 | 3.23475 | 0.132275 | 0.004775 | 2.85542 | 1.88613 | 0.089425 | 0.0302 | 0.00215 | 137.652 | 258.681 | 264.8 | 1014.76 | 3226.84 | 0.053675 | 0.05645 | 2236.5 | 0.1576 | 0.116275 | 0.773625 | 0.504075 | 0.05075 | 0.151525 | 0.26515 | 0.0551 | 0.133075 | 0.24145 | 0.133075 | 3.4687 | 0.318425 | 0.07835 | 0.1675 | 0 | 0 | 0 | 6.1034 | 0.14005 | 4.33517 | 9.37312 | 86.082 | 0.066 | 2.74507 | 0 | 5.32362 | 13.8366 | 0 | 0 | 0 | 0 | 0 | 8.91548 | 0 | 0.10385 | 2.60345 | 5.83695 | 0.221375 | 5.14597 | 9.96965 | 2.60345 | 2.80627 | 10.3194 | 53.0465 | 0.043075 | 2.60375 | 0 | 6.66568 | 27.1744 | 4.48463 | 1.81927 | 0 | 0.02485 | 0.025475 | 68.0774 | 0.0236 | 0.028125 | 0.026 | 0.038375 | 0.0482 | 0.041175 | 1.27782 | 0.000525 | 0.0006 | 0.0206 | 46.9535 | 0.0015 | 34.4192 | 0.020225 | 304.537 | 0 | 0.004725 | 0.004575 | 0.003625 | 0.003825 | 0 | 66.3198 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00165 | 0.001875 | 0 | 0 | 86.8035 | 0 | 0 | 0.00045 | 0.1703 | 0.539575 | 0.017675 | 0.0067 | 0 | 30.3264 | 0.011125 | 121.742 | 0.99835 | 0.0114 | 0.00285 | 0.12395 | 0 | 0 | 0 | 0 | 0 | 0 | 1.47765 | 12.2317 | 0 | 0 | 0 | 0 | 0 | 0.01875 | 7.63058 | 1.04947 | 4.60515 | 5.79825 | 5.178 | 5.63475 | 2.46528 | 35.3874 | 30.3112 | 0 | 6.5065 | 2.85442 | 8.85598 | 303.332 | 532.221 | 70 | 2.18657 | 4.4576 | 0 | 103.957 | 2.7215 | 4.32547 | 1.5092 | 4.47232 | 2.4089 | 6.95597 | 349.665 | 9.71917 | 19.8512 | 45.8964 | 60.7383 | 9.29218 | 6.1716 | 3.36845 | 3.5355 | 76.1769 | 104.597 | 10.1002 | 14.979 | 0.750375 | 1.53163 | 0.658875 | 0.959975 | 0.721275 | 1.21715 | 0.225975 | 0.355075 | 0 | 134.15 | 0 | 0 | 5.83047 | 4.51783 | 11.057 | 4.3458 | 18.706 | 6.71577 | 0 | 2.77095 | 723.272 | 43.5949 | 0 | 0 | 0 | 0 | 0 | 0 | 6.68682 | 350.381 | 4.99815 | 1.24733 | 8.05015 | 16.7018 | 118.547 | 38.315 | 31.5103 | 4.62643 | 18.6397 | 6.15958 | 0 | 3.36083 | 141.602 | 70.1748 | 0 | 548.306 | 118.764 | 200.466 | 169.152 | 237.777 | 332.002 | 542.566 | 393.502 | 1 | 50.016 | 1.28415 | 1.82723 | 2.57065 | 0.438 | 5.94565 | 34.8255 | 10.003 | 0 | 399.565 | 100 | 625.417 | 380.722 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 117.633 | 64.2207 | 72.5275 | 0 | 0 | 0 | 0 | 0.13795 | 0.480975 | 0.7568 | 25.3993 | 0 | 2.42287 | 0 | 11.531 | 3.6071 | 6.06468 | 5.6535 | 0.878575 | 5.97997 | 0 | 0 | 4.57 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.56422 | 4.804 | 2.21457 | 8.2108 | 0.10945 | 0.00725 | 0.002325 | 6.61385 | 0.89195 | 400.018 | 76.3335 | 0.75715 | 2838.75 | 18.72 | 1.0375 | 0.318625 | 8.7608 | 0.417325 | 79.8395 | 4.67753 | 1.35455 | 0.9545 | 0.24005 | 0.93215 | 0.05195 | 25.2011 | 198.204 | 0.425325 | 3.735 | 0.065775 | 1.56765 | 0.02865 | 1.4133 | 11.5997 | 0.951225 | 530.352 | 2.24463 | 10.105 | 0.3336 | 3.50477 | 0.101975 | 1.90522 | 14.8955 | 0.013025 | 0.005775 | 4.66175 | 0.00175 | 21.9489 | 0.501775 | 0.01615 | 0.004125 | 3.2264 | 0.0184 | 0.011725 | 0.00345 | 103.37 | -0.030225 | 92.9303 | 348.374 | 10.5827 | 109.119 | 16.5635 | 25.0302 | 32.0947 | 691.177 | 0.80805 | 151.997 | 1 | 0.12345 | 609.49 | 117.657 | 113.722 | 345.981 | 0 | 0.0043 | -0.050525 | -0.008325 | -0.00375 | 0.008125 | 1.45535 | -0.0232 | -0.00785 | 0.013275 | 7.55045 | 0.097775 | 0.02695 | 2.40238 | 0.980825 | 1821.64 | 0.190225 | 0.002025 | 8674.96 | -0.0153 | 0.0001 | 0.0006 | 7.5e-05 | 0.0001 | -0.138825 | 0 | 0.125475 | -0.043725 |
| -1 | 3033.92 | 2466.2 | 0.00126154 | -1.92e-05 | -4.23e-05 | 0.0134154 | -0.0109615 | -3.85e-06 | -5e-05 | -5e-05 | 0.0301077 | 0.00722308 | 0.565123 | 0.970919 | 59.0658 | 133.149 | 0.196054 | 0.944223 | 0.000223077 | 733.23 | 0.989262 | 58.649 | 0.574138 | 0.97175 | 199.37 | 6.33508 | 15.7985 | 3.93169 | 15.8196 | 15.7627 | 1.23488 | 2.81385 | 0.651854 | 3.21358 | -1.3876 | 0 | 0.7524 | 0.998565 | 2.30937 | 1004.76 | 39.5172 | 107.808 | 144.192 | 129.565 | 54.4923 | 484.088 | 9.12804 | 0.273462 | 0 | 6.32038 | 0.00379231 | 0.153846 | 0.0584731 | 0.0509923 | 0.0118231 | 8.31016 | 0 | 414.15 | 6.41085 | 11.9188 | 0.547785 | 0.00871154 | 7.90337 | 0.38 | 0.06215 | 0.00329615 | 106.546 | 739.5 | 9.73583 | 506.231 | 2145.31 | 6148.04 | 0.126 | 0.0998077 | 0.2135 | 2.86154 | 1.33077 | 0.129423 | 0.509462 | 0.976512 | 0.635831 | 0.150715 | 0.300431 | 0.595762 | 0.300431 | 0.796554 | 0.232485 | 0.327769 | 0 | 0 | 189.634 | 20.68 | 0.618577 | 11.005 | 24.7223 | 0.156381 | 6.99115 | 0 | 17.6069 | 37.4614 | 0 | 12.5022 | 0 | 0 | 0 | 0 | 0 | 0.280923 | 8.55 | 20.41 | 0.511077 | 10.4881 | 2206 | 1.40846 | 17.8735 | 8.55 | 10.7718 | 28.8694 | 0.158208 | 7.94769 | 4.34e-19 | 19.4342 | 63.1981 | 6.94e-18 | -5375.57 | 0.0749885 | 0.0518385 | 0.0569192 | 0.0483423 | 0.0754231 | 0.0791231 | 0.0768654 | 0.0896423 | 3.86963 | 0.00335385 | 2663.33 | 0.00198077 | 0.0603077 | 0.00294231 | 127.304 | 0.0775077 | 1056.59 | 0 | 0.0180154 | 0.0149154 | 0 | -3777.87 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00454231 | 0.0046 | -3300.27 | 0 | 0 | 0 | 0 | 0.00183077 | 0.744077 | 2.18265 | 0.01015 | 0.0255269 | 0.00123077 | 1.30267 | 110.277 | 0.00123462 | 3.04971 | 0.0319038 | 0.0128346 | 0.356419 | 0 | 0 | 0 | 0 | 1.99193 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0876692 | 17.5165 | 4.42944 | 7.29748 | 27.0309 | 46.5036 | 42.877 | 19.4831 | 154.518 | 0.0885808 | 0 | 2.02966 | 0.00102692 | 0.0536308 | 71.4897 | 0.0174077 | 0.01355 | 0.00391154 | 2.71456 | 0 | 1.97197 | 3.53237 | 0.161954 | 0.00286154 | 2.5936 | 2.2577 | 0.0849462 | 0.0218346 | 0.00109231 | 32.4558 | 331.159 | 229.164 | 971.097 | 2946.35 | 0.05685 | 0.0441385 | 1553.62 | 0.177588 | 0.0933808 | 0.943258 | 0.422535 | 0.0415077 | 0.170642 | 0.250692 | 0.0598192 | 0.122969 | 0.225738 | 0.122977 | 3.40536 | 0.318738 | 0.0941038 | 0.131177 | 0 | 0 | 0 | 6.48813 | 0.192235 | 3.36859 | 7.24623 | 85.7113 | 0.0462038 | 2.12653 | 0 | 5.3272 | 11.5349 | 0 | 0 | 0 | 0 | 0 | 9.29438 | 0 | 0.0789192 | 2.47901 | 6.36815 | 0.153985 | 3.06184 | 9.39386 | 2.47901 | 3.12203 | 8.93701 | 51.1838 | 0.0455538 | 2.38879 | -5.42e-20 | 5.95643 | 20.0414 | 2.01327 | 0.987542 | -3.47e-18 | 0.0202538 | 0.02325 | 65.3473 | 0.0256154 | 0.0220154 | 0.0209231 | 0.0402385 | 0.0382038 | 0.0428269 | 1.29983 | 0.00100769 | 0.000542308 | 0.0198615 | 48.8162 | 0.000938462 | 41.3473 | 0.0250038 | 334.713 | 0 | 0.00500385 | 0.00409231 | 0.00363846 | 0.00278077 | 0 | 66.2906 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00153846 | 0.00161923 | 0 | 0 | 86.8926 | 0 | 0 | 0.000576923 | 0.238488 | 0.664604 | 0.00265385 | 0.00823846 | 0.000392308 | 35.0583 | 0.000396154 | 119.286 | 0.930638 | 0.0105769 | 0.00412308 | 0.115485 | 0 | 0 | 0 | 0 | 0 | 0 | 1.36564 | 61.0994 | 0 | 0 | 0 | 0 | 0 | 0.0302 | 5.9927 | 1.43362 | 4.89986 | 4.75751 | 3.54192 | 5.25657 | 2.46988 | 33.2617 | 19.5568 | 0 | 6.47606 | 3.09633 | 10.6725 | 235.328 | 354.091 | 70 | 1.22274 | 4.16915 | 0 | 73.4863 | 2.87882 | 5.66531 | 0.895304 | 4.16955 | 3.04648 | 4.41728 | 355.891 | 13.8623 | 17.9324 | 57.9936 | 206.448 | 9.68742 | 5.00939 | 2.92476 | 3.9937 | 59.5532 | 74.2379 | 10.0817 | 14.9491 | 0.743765 | 1.58518 | 0.590404 | 0.918623 | 0.613612 | 1.20153 | 0.267608 | 0.273665 | 0 | 136.808 | 0 | 0 | 5.80454 | 6.1468 | 8.00363 | 3.37282 | 13.6088 | 4.99869 | 0 | 2.78556 | 734.591 | 26.8361 | 0 | 0 | 0 | 0 | 0 | 0 | 6.12151 | 201.364 | 5.72813 | 1.1682 | 4.90372 | 8.97535 | 145.53 | 42.6141 | 41.4789 | 4.08273 | 16.0236 | 5.34462 | 0 | 3.13161 | 140.351 | 57.3824 | 0 | 299.418 | 228.227 | 200.789 | 135.719 | 224.284 | 317.902 | 289.566 | 207.889 | 1 | 51.6358 | 2.54315 | 1.74233 | 2.50348 | 0.2998 | 7.09825 | 33.294 | 12.0963 | 0 | 367.756 | 100 | 633.05 | 306.274 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 157.58 | 56.3221 | 163.022 | 0 | 0 | 0 | 0 | 0.18705 | 0.729915 | 0.946008 | 2.17992 | 0 | 2.72475 | 21.2773 | 15.0441 | 0.12565 | 5.19553 | 5.34331 | 1.32758 | 5.62205 | 0 | 0 | 4.58919 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3.7762 | 4.83873 | 1.74406 | 11.2657 | 0.112777 | 0.00938462 | 0.00242692 | 8.32985 | 0.981012 | 387.519 | 71.3682 | 0.523331 | 2857.58 | 15.4519 | 1.14 | 0.219696 | 6.98582 | 0.4565 | 48.7609 | 3.83286 | 1.53457 | 1.00823 | 0.316523 | 0.927412 | 0.0717231 | 30.595 | 261.454 | 0.644404 | 5.50538 | 0.142708 | 2.26924 | 0.05765 | 2.11055 | 21.0832 | 0.9484 | 523.924 | 1.97671 | 48.5058 | 0.386977 | 15.1301 | 0.109673 | 9.86617 | 19.988 | 0.00751539 | 0.00570769 | 4.57941 | 0.00185769 | 27.4831 | 0.500296 | 0.0135077 | 0.00348846 | 2.69928 | 0.0227077 | 0.0171423 | 0.00543846 | 103.476 | 0.183708 | 98.7255 | 355.932 | 10.4723 | 116.223 | 12.816 | 20.5855 | 26.6429 | 707.948 | 1.00886 | 148.467 | 1 | 0.122546 | 620.623 | 109.697 | 60.2281 | 178.225 | -8.67e-19 | -0.00811154 | -0.0236538 | 0.00496539 | 0.0280654 | -0.00814615 | 1.44598 | -0.00451539 | -0.0199654 | 0.00603077 | 7.5661 | 0.132877 | 0.0262385 | 2.4071 | 0.985131 | 1800.56 | 0.202192 | 0.00476923 | 8730.02 | -0.00727692 | 2.31e-05 | 5.77e-05 | -5.77e-05 | 6.54e-05 | 0.0489346 | 0 | -0.0877923 | 0.00103077 |
df10.shape
(163, 591)
df10.pca.varimp(use_pandas=True)
| pc1 | pc2 | pc3 | pc4 | pc5 | pc6 | pc7 | pc8 | pc9 | ... | pc21 | pc22 | pc23 | pc24 | pc25 | pc26 | pc27 | pc28 | pc29 | pc30 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Standard deviation | 16826.660607 | 7141.607671 | 5633.216250 | 3604.831221 | 1809.942460 | 1653.929756 | 1297.314731 | 1191.221668 | 837.312653 | ... | 243.678447 | 233.905439 | 217.626109 | 201.764188 | 199.709050 | 190.896019 | 182.105753 | 178.300661 | 169.190590 | 153.426031 |
| 1 | Proportion of Variance | 0.724702 | 0.130544 | 0.081223 | 0.033261 | 0.008385 | 0.007002 | 0.004308 | 0.003632 | 0.001794 | ... | 0.000152 | 0.000140 | 0.000121 | 0.000104 | 0.000102 | 0.000093 | 0.000085 | 0.000081 | 0.000073 | 0.000060 |
| 2 | Cumulative Proportion | 0.724702 | 0.855246 | 0.936469 | 0.969729 | 0.978114 | 0.985116 | 0.989424 | 0.993056 | 0.994850 | ... | 0.998644 | 0.998784 | 0.998906 | 0.999010 | 0.999112 | 0.999205 | 0.999290 | 0.999371 | 0.999445 | 0.999505 |
3 rows × 31 columns
df10_new = df10.pca.predict(df10)
pca prediction progress: |███████████████████████████████████████████████████████| (done) 100%
from h2o.estimators.naive_bayes import H2ONaiveBayesEstimator
nv = H2ONaiveBayesEstimator()
df10_new = df10_new.cbind(df10[response10])
df10_new
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | PC11 | PC12 | PC13 | PC14 | PC15 | PC16 | PC17 | PC18 | PC19 | PC20 | PC21 | PC22 | PC23 | PC24 | PC25 | PC26 | PC27 | PC28 | PC29 | PC30 | C1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 14774.7 | 7323.35 | -691.381 | 5982.35 | -1074.31 | 205.526 | -30.7991 | -211.81 | 24.5844 | 57.4496 | 219.435 | -319.549 | -154.827 | 264.523 | -57.6311 | 344.616 | -41.355 | 62.8208 | 147.659 | -41.272 | 24.6641 | 54.6522 | 114.03 | -92.1017 | 226.306 | -335.273 | 82.9156 | 242.331 | 89.285 | 447.473 | -1 |
| 20428.5 | -8213.76 | 3720.05 | 437.661 | -354.673 | 68.3993 | -357.852 | 107.785 | 53.4299 | -116.411 | 58.907 | 49.2736 | -128.605 | 5.31764 | 74.5471 | -81.0196 | 124.133 | 141.861 | 66.1696 | -94.6196 | -29.9025 | -80.1277 | -64.6903 | -44.9624 | 78.2088 | -67.1546 | -11.4737 | 69.5446 | -52.469 | 84.5461 | -1 |
| 11150.3 | 4500.55 | 5688.07 | -1553.99 | -149.526 | 336.884 | 124.61 | 208.776 | 132.182 | 126.526 | 170.046 | -45.8854 | -42.8181 | 82.6308 | 80.735 | -55.9383 | -25.9094 | 2.27166 | 108.561 | 58.9843 | 61.3421 | 49.2498 | 9.92738 | -30.9174 | 47.3946 | -55.3258 | 26.8795 | -36.0471 | -56.3223 | 21.6616 | -1 |
| 18408.8 | 2029.12 | -1844.52 | -3810.76 | -255.792 | 34.9478 | -508.107 | 38.2165 | 59.4208 | 46.6003 | 246.573 | 171.344 | -25.1274 | -44.3528 | 53.3896 | 77.0718 | -52.7672 | 108.307 | 181.891 | 36.4165 | -94.9806 | -42.042 | 47.8338 | -76.3809 | -47.9664 | -95.9576 | -64.1112 | 122.686 | 61.7854 | 83.8555 | -1 |
| 33386 | -25604.6 | 358.693 | 647.09 | -579.68 | -294.381 | -343.498 | -117.811 | -49.9152 | 6.99423 | 397.674 | 625.167 | 404.422 | -12.9279 | 4.17488 | -317.212 | 219.33 | 12.179 | -295.701 | 1.4461 | -90.8533 | -11.7687 | -23.7741 | 77.7958 | -206.334 | -94.4746 | -28.7078 | 171.912 | 440.366 | -76.5932 | -1 |
| 25329.3 | -7432.08 | -4663.9 | 2915.08 | -1501.67 | -283.903 | 23.6793 | 686.077 | -0.300335 | -257.595 | 340.637 | 105.15 | 31.4923 | -56.9461 | -93.5362 | -300.612 | 393.193 | 88.0948 | -123.613 | -39.6657 | -46.2088 | -253.398 | 49.0059 | -167.346 | 60.2594 | -30.1163 | -58.5558 | 144.739 | 64.5846 | -114.227 | -1 |
| 11184 | 6942.16 | 4637.13 | 1568.12 | 468.015 | 427.557 | -376.449 | 834.661 | 119.87 | 405.886 | -127.076 | 106.812 | 16.3848 | -111.048 | 47.1737 | -89.16 | 31.4201 | -36.2913 | 30.3903 | -72.7518 | 74.7805 | 20.7573 | -38.8937 | -62.785 | 35.4054 | -43.3193 | 81.3423 | 12.7291 | 49.2515 | 18.7822 | -1 |
| 14204 | 1754.54 | 4296.75 | -8414.04 | 488.103 | 250.898 | -238.72 | 301.769 | 193.601 | -165.214 | -329.601 | -524.031 | -59.3444 | 422.197 | 24.559 | -500.918 | -144.832 | 24.2673 | -102.918 | 178.567 | -209.033 | 151.23 | -177.397 | -37.9021 | 125.64 | -131.704 | 199.37 | 16.4481 | -19.1788 | -13.5258 | -1 |
| 14224.9 | 833.179 | 4328.74 | -3078.28 | -204.899 | 193.323 | -131.38 | 351 | 122.416 | -107.912 | 122.541 | 79.7181 | -25.2138 | 145.583 | 127.906 | -14.0771 | -53.6315 | 22.1552 | -14.4545 | -54.3269 | -115.689 | 57.9734 | -33.7068 | 6.89065 | 104.751 | -31.4472 | 45.9479 | -79.9241 | 85.8581 | 8.79863 | -1 |
h2o.download_csv(df10_new,"C:\\Users\\Admin\\Desktop\\FMT")
'C:\\Users\\Admin\\Desktop\\FMT\\unknown'
pca_df5 = pd.read_csv('PCA_US.csv')
print(pca_df5.shape)
pca_df5.head()
(162, 31)
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | ... | PC22 | PC23 | PC24 | PC25 | PC26 | PC27 | PC28 | PC29 | PC30 | C1 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 14774.71273 | 7323.350313 | -691.381283 | 5982.347079 | -1074.305804 | 205.525955 | -30.799136 | -211.810216 | 24.584420 | 57.449576 | ... | 54.652161 | 114.029849 | -92.101749 | 226.306172 | -335.273350 | 82.915611 | 242.331462 | 89.285001 | 447.472545 | -1 |
| 1 | 20428.46443 | -8213.759010 | 3720.053854 | 437.661051 | -354.672685 | 68.399348 | -357.851676 | 107.785475 | 53.429941 | -116.411161 | ... | -80.127721 | -64.690261 | -44.962367 | 78.208791 | -67.154641 | -11.473744 | 69.544556 | -52.468990 | 84.546072 | -1 |
| 2 | 11150.25113 | 4500.554599 | 5688.074855 | -1553.992810 | -149.526166 | 336.884172 | 124.610237 | 208.776390 | 132.181780 | 126.526318 | ... | 49.249823 | 9.927382 | -30.917402 | 47.394630 | -55.325773 | 26.879474 | -36.047118 | -56.322319 | 21.661590 | -1 |
| 3 | 18408.77977 | 2029.118644 | -1844.523659 | -3810.764088 | -255.792139 | 34.947846 | -508.107415 | 38.216501 | 59.420790 | 46.600315 | ... | -42.041995 | 47.833840 | -76.380924 | -47.966431 | -95.957632 | -64.111240 | 122.685895 | 61.785433 | 83.855547 | -1 |
| 4 | 33386.04956 | -25604.602080 | 358.693288 | 647.090173 | -579.679739 | -294.381493 | -343.497766 | -117.811212 | -49.915170 | 6.994228 | ... | -11.768728 | -23.774073 | 77.795802 | -206.334228 | -94.474616 | -28.707845 | 171.912059 | 440.366250 | -76.593234 | -1 |
5 rows × 31 columns
pca_df5.dtypes
PC1 float64 PC2 float64 PC3 float64 PC4 float64 PC5 float64 PC6 float64 PC7 float64 PC8 float64 PC9 float64 PC10 float64 PC11 float64 PC12 float64 PC13 float64 PC14 float64 PC15 float64 PC16 float64 PC17 float64 PC18 float64 PC19 float64 PC20 float64 PC21 float64 PC22 float64 PC23 float64 PC24 float64 PC25 float64 PC26 float64 PC27 float64 PC28 float64 PC29 float64 PC30 float64 C1 int64 dtype: object
pca_df5['C1'] = pca_df3['C1'].apply(str)
print()
print(pca_df5.dtypes)
pca_df5
PC1 float64 PC2 float64 PC3 float64 PC4 float64 PC5 float64 PC6 float64 PC7 float64 PC8 float64 PC9 float64 PC10 float64 PC11 float64 PC12 float64 PC13 float64 PC14 float64 PC15 float64 PC16 float64 PC17 float64 PC18 float64 PC19 float64 PC20 float64 PC21 float64 PC22 float64 PC23 float64 PC24 float64 PC25 float64 PC26 float64 PC27 float64 PC28 float64 PC29 float64 PC30 float64 C1 object dtype: object
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | ... | PC22 | PC23 | PC24 | PC25 | PC26 | PC27 | PC28 | PC29 | PC30 | C1 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 14774.71273 | 7323.350313 | -691.381283 | 5982.347079 | -1074.305804 | 205.525955 | -30.799136 | -211.810216 | 24.584420 | 57.449576 | ... | 54.652161 | 114.029849 | -92.101749 | 226.306172 | -335.273350 | 82.915611 | 242.331462 | 89.285001 | 447.472545 | -1 |
| 1 | 20428.46443 | -8213.759010 | 3720.053854 | 437.661051 | -354.672685 | 68.399348 | -357.851676 | 107.785475 | 53.429941 | -116.411161 | ... | -80.127721 | -64.690261 | -44.962367 | 78.208791 | -67.154641 | -11.473744 | 69.544556 | -52.468990 | 84.546072 | 1 |
| 2 | 11150.25113 | 4500.554599 | 5688.074855 | -1553.992810 | -149.526166 | 336.884172 | 124.610237 | 208.776390 | 132.181780 | 126.526318 | ... | 49.249823 | 9.927382 | -30.917402 | 47.394630 | -55.325773 | 26.879474 | -36.047118 | -56.322319 | 21.661590 | -1 |
| 3 | 18408.77977 | 2029.118644 | -1844.523659 | -3810.764088 | -255.792139 | 34.947846 | -508.107415 | 38.216501 | 59.420790 | 46.600315 | ... | -42.041995 | 47.833840 | -76.380924 | -47.966431 | -95.957632 | -64.111240 | 122.685895 | 61.785433 | 83.855547 | -1 |
| 4 | 33386.04956 | -25604.602080 | 358.693288 | 647.090173 | -579.679739 | -294.381493 | -343.497766 | -117.811212 | -49.915170 | 6.994228 | ... | -11.768728 | -23.774073 | 77.795802 | -206.334228 | -94.474616 | -28.707845 | 171.912059 | 440.366250 | -76.593234 | -1 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 157 | 23649.94607 | 245.554637 | -9516.483957 | 1884.296891 | -2522.490524 | -520.158445 | 247.900766 | 1662.132711 | 26.261804 | -89.390266 | ... | -149.442182 | -562.420638 | 41.821990 | -78.067613 | 230.299307 | 53.107860 | 7.747609 | -22.943471 | 63.344970 | -1 |
| 158 | 12368.62955 | 7407.745324 | 1249.516723 | 716.930556 | -188.175848 | 297.582602 | -169.132606 | -124.727069 | 80.153446 | 122.043642 | ... | 226.811002 | 301.144043 | 147.351114 | -411.352718 | 70.746970 | -63.199404 | 106.770547 | 79.492205 | 186.345698 | -1 |
| 159 | 19741.96129 | -5571.549649 | 599.034817 | 2528.639219 | -1757.563706 | 14.349120 | 2389.393093 | 566.007968 | -28.931107 | 1248.543588 | ... | 114.099359 | 116.318842 | 202.445591 | 65.899293 | 307.634453 | -227.140073 | 183.738292 | -281.768917 | 122.694077 | -1 |
| 160 | 15045.77307 | -1309.918393 | 5281.308860 | -2287.706208 | 110.549261 | 212.974885 | -179.321402 | 389.078083 | 77.214842 | 206.045505 | ... | -438.068691 | 223.237109 | 223.145786 | 111.093162 | -51.419643 | 108.373399 | 75.223102 | -229.922915 | -100.697957 | -1 |
| 161 | 12423.85600 | 2026.366733 | 5976.462633 | -4388.763662 | -377.408594 | 94.083121 | -894.399779 | 432.428980 | 140.197258 | -184.367689 | ... | -354.187316 | 326.635223 | 153.894906 | -299.152090 | -35.453485 | -37.043754 | 58.853467 | 169.067965 | 105.128250 | -1 |
162 rows × 31 columns
pca_df6= pca_df5.drop('C1', axis=1)
y = pca_df5['C1']
X = pca_df6
classifier = Classification(
predictor='svm',
params= {},
cv_folds=2,
epochs=5)
classifier.fit(X, y)
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Started LuciferML
Checking if labels or features are categorical! [*]
Features are not categorical [ ✓ ]
Labels are Categorical [*]
Encoding Labels
Encoding Labels Done [ ✓ ]
Checking for Categorical Variables Done [ ✓ ]
Checking for Sparse Matrix [*]
Splitting Data into Train and Validation Sets [*]
Splitting Done [ ✓ ]
Scaling Training and Test Sets [*]
Scaling Done [ ✓ ]
Training Support Vector Machine on Training Set [*]
Model Training Done [ ✓ ]
Predicting Data [*]
Data Prediction Done [ ✓ ]
Making Confusion Matrix [*]
[[32 0]
[ 1 0]]
Confusion Matrix Done [ ✓ ] Evaluating Model Performance [*] Validation Accuracy is : 0.9696969696969697 Evaluating Model Performance [ ✓ ] Applying K-Fold Cross Validation [*] Accuracy: 91.48 % Standard Deviation: 0.71 % K-Fold Cross Validation [ ✓ ] Complete [ ✓ ] Time Elapsed : 0.5725023746490479 seconds
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
Y = data1['Pass/Fail']
X = data2
test_size = 0.30
seed = 7
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size, random_state=seed)
type(X_train)
pandas.core.frame.DataFrame
pipeline = Pipeline([
('scaler',StandardScaler()),
('clf', LogisticRegression())])
pipeline.fit(X_train,Y_train)
Pipeline(steps=[('scaler', StandardScaler()), ('clf', LogisticRegression())])
from sklearn import metrics
Y_predict = pipeline.predict(X_test)
model_score = pipeline.score(X_test, Y_test)
print(model_score)
print(metrics.confusion_matrix(Y_test, Y_predict))
0.8938428874734607 [[415 33] [ 17 6]]
y = data1['Pass/Fail']
X = data2
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler
X_train, X_test, y_train, y_test = train_test_split( X, y, random_state = 0)
scaler = MinMaxScaler().fit( X_train)
X_train_scaled = scaler.transform( X_train)
svm = SVC()
svm.fit( X_train_scaled, y_train)
X_test_scaled = scaler.transform( X_test)
print(" Test score: {:.2f}".format( svm.score( X_test_scaled, y_test)))
Test score: 0.95
from sklearn.pipeline import Pipeline
pipe = Pipeline([(" scaler", MinMaxScaler()), (" svm", SVC())])
pipe.fit( X_train, y_train)
Pipeline(steps=[(' scaler', MinMaxScaler()), (' svm', SVC())])
print(" Test score: {:.2f}". format( pipe.score( X_test, y_test)))
Test score: 0.95
y_pred = pipe.predict(X_test)
from sklearn import metrics
print(metrics.classification_report(y_test, y_pred))
precision recall f1-score support
-1 0.95 1.00 0.97 371
1 0.00 0.00 0.00 21
accuracy 0.95 392
macro avg 0.47 0.50 0.49 392
weighted avg 0.90 0.95 0.92 392
from sklearn.pipeline import make_pipeline
pipe = make_pipeline( MinMaxScaler(), (SVC()))
print(" Pipeline steps:\ n{}". format( pipe.steps))
Pipeline steps:\ n[('minmaxscaler', MinMaxScaler()), ('svc', SVC())]
pipe.fit( X_train, y_train)
Pipeline(steps=[('minmaxscaler', MinMaxScaler()), ('svc', SVC())])
print(" Test score: {:.2f}". format( pipe.score( X_test, y_test)))
Test score: 0.95
pca_df.head()
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | ... | PC42 | PC43 | PC44 | PC45 | PC46 | PC47 | PC48 | PC49 | PC50 | C591 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | -592.924304 | 20.917196 | 110.389292 | -29.780230 | 182.517317 | 487.757737 | -193.233225 | 462.333997 | 340.492422 | -130.888968 | ... | -121.195286 | 184.723652 | -193.295096 | -46.597260 | 210.840342 | -74.015457 | 9.571485 | -51.333020 | -76.935605 | -1 |
| 1 | -11534.534860 | -5286.104909 | -3786.984314 | -636.457862 | 85.753879 | 328.369646 | 127.425188 | -46.526547 | 32.036950 | 351.167986 | ... | 94.554459 | 65.300338 | -59.673060 | -0.814107 | 50.672109 | -97.912562 | 86.104438 | 12.856700 | -77.827252 | -1 |
| 2 | -12386.084860 | -1929.815775 | -4272.166834 | 1543.516825 | 167.490946 | -479.343759 | -382.872794 | -48.723428 | -40.313318 | -334.317904 | ... | 159.183024 | 117.706921 | 175.423993 | -108.203004 | -89.194043 | -111.213116 | 76.321301 | 10.324508 | -38.461348 | -1 |
| 3 | -12561.346130 | -3499.871039 | -4118.211872 | 1909.034331 | 264.268464 | -331.682796 | 237.089044 | -24.837079 | -88.847628 | 187.667223 | ... | -24.954219 | 27.369188 | 18.581551 | 41.358416 | 66.885104 | 67.073605 | 14.202763 | 3.235745 | -49.182694 | 1 |
| 4 | -13386.666180 | -2856.942202 | -1133.308163 | 1537.090339 | -669.983465 | 152.870526 | 295.297500 | -62.946769 | 37.600294 | 59.350230 | ... | -14.740262 | 33.326744 | -2.514542 | 25.332467 | 55.888198 | 72.388642 | 17.873116 | 11.014890 | -23.420128 | -1 |
5 rows × 51 columns
pca_df2.head()
| PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | ... | PC41 | PC42 | PC43 | PC44 | PC45 | PC46 | PC47 | PC48 | PC49 | PC50 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | -592.924304 | 20.917196 | 110.389292 | -29.780230 | 182.517317 | 487.757737 | -193.233225 | 462.333997 | 340.492422 | -130.888968 | ... | 135.530242 | -121.195286 | 184.723652 | -193.295096 | -46.597260 | 210.840342 | -74.015457 | 9.571485 | -51.333020 | -76.935605 |
| 1 | -11534.534860 | -5286.104909 | -3786.984314 | -636.457862 | 85.753879 | 328.369646 | 127.425188 | -46.526547 | 32.036950 | 351.167986 | ... | 129.984577 | 94.554459 | 65.300338 | -59.673060 | -0.814107 | 50.672109 | -97.912562 | 86.104438 | 12.856700 | -77.827252 |
| 2 | -12386.084860 | -1929.815775 | -4272.166834 | 1543.516825 | 167.490946 | -479.343759 | -382.872794 | -48.723428 | -40.313318 | -334.317904 | ... | 231.367742 | 159.183024 | 117.706921 | 175.423993 | -108.203004 | -89.194043 | -111.213116 | 76.321301 | 10.324508 | -38.461348 |
| 3 | -12561.346130 | -3499.871039 | -4118.211872 | 1909.034331 | 264.268464 | -331.682796 | 237.089044 | -24.837079 | -88.847628 | 187.667223 | ... | 45.113478 | -24.954219 | 27.369188 | 18.581551 | 41.358416 | 66.885104 | 67.073605 | 14.202763 | 3.235745 | -49.182694 |
| 4 | -13386.666180 | -2856.942202 | -1133.308163 | 1537.090339 | -669.983465 | 152.870526 | 295.297500 | -62.946769 | 37.600294 | 59.350230 | ... | -4.553109 | -14.740262 | 33.326744 | -2.514542 | 25.332467 | 55.888198 | 72.388642 | 17.873116 | 11.014890 | -23.420128 |
5 rows × 50 columns
y1 = pca_df['C591']
X1 = pca_df2
test_size = 0.30
seed = 8
X1_train, X1_test, y1_train, y1_test = train_test_split(X1, y1, test_size=test_size, random_state=seed)
type(X1_train)
pandas.core.frame.DataFrame
pipeline = Pipeline([
('scaler',StandardScaler()),
('clf', LogisticRegression())])
pipeline.fit(X1_train,y1_train)
Pipeline(steps=[('scaler', StandardScaler()), ('clf', LogisticRegression())])
from sklearn import metrics
y1_predict = pipeline.predict(X1_test)
model_score = pipeline.score(X1_test, y1_test)
print(model_score)
print(metrics.confusion_matrix(y1_test, y1_predict))
0.940552016985138 [[442 2] [ 26 1]]
y2 = pca_df3['C1']
X2 = pca_df4
test_size = 0.30
seed = 7
X2_train, X2_test, y2_train, y2_test = train_test_split(X2, y2, test_size=test_size, random_state=seed)
type(X2_train)
pandas.core.frame.DataFrame
pipeline2 = Pipeline([
('scaler',StandardScaler()),
('clf', LogisticRegression())])
pipeline2.fit(X2_train,y2_train)
Pipeline(steps=[('scaler', StandardScaler()), ('clf', LogisticRegression())])
from sklearn import metrics
y2_predict = pipeline2.predict(X2_test)
model_score = pipeline2.score(X2_test, y2_test)
print(model_score)
print(metrics.confusion_matrix(y2_test, y2_predict))
0.6934426229508197 [[213 91] [ 96 210]]
y3 = pca_df5['C1']
X3 = pca_df6
test_size = 0.30
seed = 7
X3_train, X3_test, y3_train, y3_test = train_test_split(X3, y3, test_size=test_size, random_state=seed)
type(X3_train)
pandas.core.frame.DataFrame
pipeline3 = Pipeline([
('scaler',StandardScaler()),
('clf', LogisticRegression())])
pipeline3.fit(X3_train,y3_train)
Pipeline(steps=[('scaler', StandardScaler()), ('clf', LogisticRegression())])
from sklearn import metrics
y3_predict = pipeline3.predict(X3_test)
model_score = pipeline3.score(X3_test, y3_test)
print(model_score)
print(metrics.confusion_matrix(y3_test, y3_predict))
0.8571428571428571 [[42 1] [ 6 0]]
Classification algorithms gave best accuracy score for Random Oversampling Data
1.Classification score on Original data : 0.92 2.Classification score on Random Over Sampling data : 1 3.Classification score on Under Sampling data : 0.81 4.Classification score on PCA original data : 0.93 5.Classification score on PCA Random Over Sampling data : 0.93 6.Classification score on PCA Under Sampling data : 0.91 7.Classification score on Pipeline data : 0.95 8.Classification score on PCA Pipeline data : 0.94 9.Classification score on PCA Pipeline Random Over Sampling data : 0.69 10.Classification score on PCA Pipeline Under Sampling data : 0.85
Now lets check the score generated by the AUTO ML by H2O
import h2o
from h2o.automl import H2OAutoML
h2o.init()
Checking whether there is an H2O instance running at http://localhost:54321 . connected.
| H2O_cluster_uptime: | 56 mins 05 secs |
| H2O_cluster_timezone: | Asia/Kolkata |
| H2O_data_parsing_timezone: | UTC |
| H2O_cluster_version: | 3.34.0.3 |
| H2O_cluster_version_age: | 1 month and 29 days |
| H2O_cluster_name: | H2O_from_python_Admin_ta4v05 |
| H2O_cluster_total_nodes: | 1 |
| H2O_cluster_free_memory: | 1.474 Gb |
| H2O_cluster_total_cores: | 8 |
| H2O_cluster_allowed_cores: | 8 |
| H2O_cluster_status: | locked, healthy |
| H2O_connection_url: | http://localhost:54321 |
| H2O_connection_proxy: | {"http": null, "https": null} |
| H2O_internal_security: | False |
| H2O_API_Extensions: | Amazon S3, Algos, AutoML, Core V3, TargetEncoder, Core V4 |
| Python_version: | 3.8.8 final |
import pandas as pd
df = h2o.import_file("C:\\Users\\Admin\\Desktop\\FMT\\signal-data1.csv")
Parse progress: |████████████████████████████████████████████████████████████████| (done) 100%
df['C591'] = df['C591'].asfactor()
df['C591'].describe()
Rows:1568 Cols:1
| C591 | |
|---|---|
| type | enum |
| mins | |
| mean | |
| maxs | |
| sigma | |
| zeros | |
| missing | 1 |
| 0 | |
| 1 | -1 |
| 2 | -1 |
| 3 | 1 |
| 4 | -1 |
| 5 | -1 |
| 6 | -1 |
| 7 | -1 |
| 8 | -1 |
| 9 | -1 |
y = "C591"
x = df.columns
x.remove(y)
aml = H2OAutoML(max_models = 10, seed = 1)
aml.train(x = x, y = y, training_frame = df)
AutoML progress: |█ 11:22:08.759: AutoML: XGBoost is not available; skipping it. 11:22:08.759: Step 'best_of_family_xgboost' not defined in provider 'StackedEnsemble': skipping it. 11:22:08.759: Step 'all_xgboost' not defined in provider 'StackedEnsemble': skipping it. ██████████████████████████████████████████████████████████████| (done) 100% Model Details ============= H2OStackedEnsembleEstimator : Stacked Ensemble Model Key: StackedEnsemble_AllModels_2_AutoML_7_20211207_112208 No model summary for this model ModelMetricsBinomialGLM: stackedensemble ** Reported on train data. ** MSE: 0.010655503365430316 RMSE: 0.10322549765164767 LogLoss: 0.06477170693092947 Null degrees of freedom: 1566 Residual degrees of freedom: 1560 Null deviance: 765.1453471374808 Residual deviance: 202.99452952153297 AIC: 216.99452952153297 AUC: 1.0 AUCPR: 1.0 Gini: 1.0 Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.3781879301747034:
| -1 | 1 | Error | Rate | ||
|---|---|---|---|---|---|
| 0 | -1 | 1463.0 | 0.0 | 0.0 | (0.0/1463.0) |
| 1 | 1 | 0.0 | 104.0 | 0.0 | (0.0/104.0) |
| 2 | Total | 1463.0 | 104.0 | 0.0 | (0.0/1567.0) |
Maximum Metrics: Maximum metrics at their respective thresholds
| metric | threshold | value | idx | |
|---|---|---|---|---|
| 0 | max f1 | 0.378188 | 1.000000 | 93.0 |
| 1 | max f2 | 0.378188 | 1.000000 | 93.0 |
| 2 | max f0point5 | 0.378188 | 1.000000 | 93.0 |
| 3 | max accuracy | 0.378188 | 1.000000 | 93.0 |
| 4 | max precision | 0.864363 | 1.000000 | 0.0 |
| 5 | max recall | 0.378188 | 1.000000 | 93.0 |
| 6 | max specificity | 0.864363 | 1.000000 | 0.0 |
| 7 | max absolute_mcc | 0.378188 | 1.000000 | 93.0 |
| 8 | max min_per_class_accuracy | 0.378188 | 1.000000 | 93.0 |
| 9 | max mean_per_class_accuracy | 0.378188 | 1.000000 | 93.0 |
| 10 | max tns | 0.864363 | 1463.000000 | 0.0 |
| 11 | max fns | 0.864363 | 103.000000 | 0.0 |
| 12 | max fps | 0.002032 | 1463.000000 | 399.0 |
| 13 | max tps | 0.378188 | 104.000000 | 93.0 |
| 14 | max tnr | 0.864363 | 1.000000 | 0.0 |
| 15 | max fnr | 0.864363 | 0.990385 | 0.0 |
| 16 | max fpr | 0.002032 | 1.000000 | 399.0 |
| 17 | max tpr | 0.378188 | 1.000000 | 93.0 |
Gains/Lift Table: Avg response rate: 6.64 %, avg score: 7.91 %
| group | cumulative_data_fraction | lower_threshold | lift | cumulative_lift | response_rate | score | cumulative_response_rate | cumulative_score | capture_rate | cumulative_capture_rate | gain | cumulative_gain | kolmogorov_smirnov | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 0.009572 | 0.775900 | 15.067308 | 15.067308 | 1.000000 | 0.806729 | 1.000000 | 0.806729 | 0.144231 | 0.144231 | 1406.730769 | 1406.730769 | 0.144231 |
| 1 | 2 | 0.019783 | 0.736406 | 15.067308 | 15.067308 | 1.000000 | 0.756038 | 1.000000 | 0.780566 | 0.153846 | 0.298077 | 1406.730769 | 1406.730769 | 0.298077 |
| 2 | 3 | 0.029994 | 0.685778 | 15.067308 | 15.067308 | 1.000000 | 0.703435 | 1.000000 | 0.754308 | 0.153846 | 0.451923 | 1406.730769 | 1406.730769 | 0.451923 |
| 3 | 4 | 0.039566 | 0.643295 | 15.067308 | 15.067308 | 1.000000 | 0.661430 | 1.000000 | 0.731838 | 0.144231 | 0.596154 | 1406.730769 | 1406.730769 | 0.596154 |
| 4 | 5 | 0.049777 | 0.591995 | 15.067308 | 15.067308 | 1.000000 | 0.619331 | 1.000000 | 0.708759 | 0.153846 | 0.750000 | 1406.730769 | 1406.730769 | 0.750000 |
| 5 | 6 | 0.099553 | 0.119228 | 5.022436 | 10.044872 | 0.333333 | 0.275880 | 0.666667 | 0.492320 | 0.250000 | 1.000000 | 402.243590 | 904.487179 | 0.964457 |
| 6 | 7 | 0.149968 | 0.084378 | 0.000000 | 6.668085 | 0.000000 | 0.100286 | 0.442553 | 0.360530 | 0.000000 | 1.000000 | -100.000000 | 566.808511 | 0.910458 |
| 7 | 8 | 0.199745 | 0.062417 | 0.000000 | 5.006390 | 0.000000 | 0.073415 | 0.332268 | 0.288980 | 0.000000 | 1.000000 | -100.000000 | 400.638978 | 0.857143 |
| 8 | 9 | 0.299936 | 0.043460 | 0.000000 | 3.334043 | 0.000000 | 0.051061 | 0.221277 | 0.209505 | 0.000000 | 1.000000 | -100.000000 | 233.404255 | 0.749829 |
| 9 | 10 | 0.399489 | 0.033875 | 0.000000 | 2.503195 | 0.000000 | 0.038295 | 0.166134 | 0.166839 | 0.000000 | 1.000000 | -100.000000 | 150.319489 | 0.643199 |
| 10 | 11 | 0.499681 | 0.028137 | 0.000000 | 2.001277 | 0.000000 | 0.030862 | 0.132822 | 0.139574 | 0.000000 | 1.000000 | -100.000000 | 100.127714 | 0.535885 |
| 11 | 12 | 0.599872 | 0.023922 | 0.000000 | 1.667021 | 0.000000 | 0.025988 | 0.110638 | 0.120603 | 0.000000 | 1.000000 | -100.000000 | 66.702128 | 0.428571 |
| 12 | 13 | 0.699426 | 0.020312 | 0.000000 | 1.429745 | 0.000000 | 0.022009 | 0.094891 | 0.106570 | 0.000000 | 1.000000 | -100.000000 | 42.974453 | 0.321941 |
| 13 | 14 | 0.799617 | 0.017008 | 0.000000 | 1.250599 | 0.000000 | 0.018705 | 0.083001 | 0.095560 | 0.000000 | 1.000000 | -100.000000 | 25.059856 | 0.214627 |
| 14 | 15 | 0.899809 | 0.013715 | 0.000000 | 1.111348 | 0.000000 | 0.015391 | 0.073759 | 0.086634 | 0.000000 | 1.000000 | -100.000000 | 11.134752 | 0.107314 |
| 15 | 16 | 1.000000 | 0.002032 | 0.000000 | 1.000000 | 0.000000 | 0.011025 | 0.066369 | 0.079058 | 0.000000 | 1.000000 | -100.000000 | 0.000000 | 0.000000 |
ModelMetricsBinomialGLM: stackedensemble ** Reported on cross-validation data. ** MSE: 0.05933091549704305 RMSE: 0.2435793823315985 LogLoss: 0.22010535488103422 Null degrees of freedom: 1566 Residual degrees of freedom: 1560 Null deviance: 768.3832736109661 Residual deviance: 689.8101821971611 AIC: 703.8101821971611 AUC: 0.7544659288080341 AUCPR: 0.17039122145046848 Gini: 0.5089318576160682 Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.12457775725268817:
| -1 | 1 | Error | Rate | ||
|---|---|---|---|---|---|
| 0 | -1 | 1297.0 | 166.0 | 0.1135 | (166.0/1463.0) |
| 1 | 1 | 59.0 | 45.0 | 0.5673 | (59.0/104.0) |
| 2 | Total | 1356.0 | 211.0 | 0.1436 | (225.0/1567.0) |
Maximum Metrics: Maximum metrics at their respective thresholds
| metric | threshold | value | idx | |
|---|---|---|---|---|
| 0 | max f1 | 0.124578 | 0.285714 | 145.0 |
| 1 | max f2 | 0.067133 | 0.414236 | 225.0 |
| 2 | max f0point5 | 0.162406 | 0.253067 | 110.0 |
| 3 | max accuracy | 0.651951 | 0.932993 | 0.0 |
| 4 | max precision | 0.283425 | 0.277778 | 34.0 |
| 5 | max recall | 0.010194 | 1.000000 | 388.0 |
| 6 | max specificity | 0.651951 | 0.999316 | 0.0 |
| 7 | max absolute_mcc | 0.067133 | 0.237905 | 225.0 |
| 8 | max min_per_class_accuracy | 0.058642 | 0.706767 | 242.0 |
| 9 | max mean_per_class_accuracy | 0.053899 | 0.721252 | 252.0 |
| 10 | max tns | 0.651951 | 1462.000000 | 0.0 |
| 11 | max fns | 0.651951 | 104.000000 | 0.0 |
| 12 | max fps | 0.000780 | 1463.000000 | 399.0 |
| 13 | max tps | 0.010194 | 104.000000 | 388.0 |
| 14 | max tnr | 0.651951 | 0.999316 | 0.0 |
| 15 | max fnr | 0.651951 | 1.000000 | 0.0 |
| 16 | max fpr | 0.000780 | 1.000000 | 399.0 |
| 17 | max tpr | 0.010194 | 1.000000 | 388.0 |
Gains/Lift Table: Avg response rate: 6.64 %, avg score: 6.65 %
| group | cumulative_data_fraction | lower_threshold | lift | cumulative_lift | response_rate | score | cumulative_response_rate | cumulative_score | capture_rate | cumulative_capture_rate | gain | cumulative_gain | kolmogorov_smirnov | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 0.009572 | 0.358701 | 2.008974 | 2.008974 | 0.133333 | 0.479863 | 0.133333 | 0.479863 | 0.019231 | 0.019231 | 100.897436 | 100.897436 | 0.010345 |
| 1 | 2 | 0.019783 | 0.293881 | 5.650240 | 3.888337 | 0.375000 | 0.329366 | 0.258065 | 0.402187 | 0.057692 | 0.076923 | 465.024038 | 288.833747 | 0.061202 |
| 2 | 3 | 0.029994 | 0.262108 | 3.766827 | 3.846972 | 0.250000 | 0.275820 | 0.255319 | 0.359169 | 0.038462 | 0.115385 | 276.682692 | 284.697218 | 0.091461 |
| 3 | 4 | 0.039566 | 0.239635 | 3.013462 | 3.645316 | 0.200000 | 0.252837 | 0.241935 | 0.333443 | 0.028846 | 0.144231 | 201.346154 | 264.531638 | 0.112105 |
| 4 | 5 | 0.049777 | 0.217366 | 0.941707 | 3.090730 | 0.062500 | 0.227074 | 0.205128 | 0.311624 | 0.009615 | 0.153846 | -5.829327 | 209.072978 | 0.111467 |
| 5 | 6 | 0.099553 | 0.150427 | 3.670242 | 3.380486 | 0.243590 | 0.181987 | 0.224359 | 0.246806 | 0.182692 | 0.336538 | 267.024162 | 238.048570 | 0.253832 |
| 6 | 7 | 0.149968 | 0.115695 | 2.288705 | 3.013462 | 0.151899 | 0.131687 | 0.200000 | 0.208106 | 0.115385 | 0.451923 | 128.870497 | 201.346154 | 0.323420 |
| 7 | 8 | 0.199745 | 0.089531 | 1.159024 | 2.551333 | 0.076923 | 0.099404 | 0.169329 | 0.181017 | 0.057692 | 0.509615 | 15.902367 | 155.133325 | 0.331898 |
| 8 | 9 | 0.299936 | 0.063583 | 1.823432 | 2.308183 | 0.121019 | 0.075212 | 0.153191 | 0.145674 | 0.182692 | 0.692308 | 82.343214 | 130.818331 | 0.420264 |
| 9 | 10 | 0.399489 | 0.048300 | 0.869268 | 1.949604 | 0.057692 | 0.054826 | 0.129393 | 0.123035 | 0.086538 | 0.778846 | -13.073225 | 94.960371 | 0.406324 |
| 10 | 11 | 0.499681 | 0.040029 | 0.383880 | 1.635659 | 0.025478 | 0.044027 | 0.108557 | 0.107193 | 0.038462 | 0.817308 | -61.611955 | 63.565920 | 0.340206 |
| 11 | 12 | 0.599872 | 0.033624 | 0.575821 | 1.458644 | 0.038217 | 0.036630 | 0.096809 | 0.095407 | 0.057692 | 0.875000 | -42.417932 | 45.864362 | 0.294686 |
| 12 | 13 | 0.699426 | 0.029184 | 0.193171 | 1.278522 | 0.012821 | 0.031542 | 0.084854 | 0.086317 | 0.019231 | 0.894231 | -80.682939 | 27.852155 | 0.208653 |
| 13 | 14 | 0.799617 | 0.024358 | 0.671791 | 1.202499 | 0.044586 | 0.026854 | 0.079808 | 0.078866 | 0.067308 | 0.961538 | -32.820921 | 20.249862 | 0.173432 |
| 14 | 15 | 0.899809 | 0.017662 | 0.191940 | 1.089975 | 0.012739 | 0.021150 | 0.072340 | 0.072440 | 0.019231 | 0.980769 | -80.805977 | 8.997545 | 0.086716 |
| 15 | 16 | 1.000000 | 0.000634 | 0.191940 | 1.000000 | 0.012739 | 0.012830 | 0.066369 | 0.066467 | 0.019231 | 1.000000 | -80.805977 | 0.000000 | 0.000000 |
lb = aml.leaderboard
lb.head(rows=lb.nrows)
| model_id | auc | logloss | aucpr | mean_per_class_error | rmse | mse |
|---|---|---|---|---|---|---|
| StackedEnsemble_AllModels_2_AutoML_7_20211207_112208 | 0.754466 | 0.220105 | 0.170391 | 0.340387 | 0.243579 | 0.0593309 |
| StackedEnsemble_BestOfFamily_3_AutoML_7_20211207_112208 | 0.752902 | 0.22088 | 0.16726 | 0.275971 | 0.243955 | 0.0595142 |
| StackedEnsemble_BestOfFamily_5_AutoML_7_20211207_112208 | 0.748459 | 0.222478 | 0.162157 | 0.311767 | 0.243417 | 0.0592518 |
| StackedEnsemble_AllModels_5_AutoML_7_20211207_112208 | 0.746898 | 0.221455 | 0.166695 | 0.336535 | 0.242744 | 0.0589246 |
| StackedEnsemble_BestOfFamily_2_AutoML_7_20211207_112208 | 0.746681 | 0.22087 | 0.172395 | 0.304567 | 0.24298 | 0.0590391 |
| StackedEnsemble_AllModels_1_AutoML_7_20211207_112208 | 0.74556 | 0.221179 | 0.170215 | 0.329358 | 0.243241 | 0.0591664 |
| GBM_3_AutoML_7_20211207_112208 | 0.740625 | 0.227787 | 0.168979 | 0.3562 | 0.245331 | 0.0601871 |
| StackedEnsemble_AllModels_3_AutoML_7_20211207_112208 | 0.737841 | 0.223635 | 0.165792 | 0.330679 | 0.244728 | 0.0598918 |
| GBM_1_AutoML_7_20211207_112208 | 0.731729 | 0.221889 | 0.171374 | 0.32856 | 0.242213 | 0.058667 |
| GBM_4_AutoML_7_20211207_112208 | 0.728147 | 0.233628 | 0.161543 | 0.38409 | 0.24538 | 0.0602113 |
| StackedEnsemble_BestOfFamily_1_AutoML_7_20211207_112208 | 0.72071 | 0.223738 | 0.162217 | 0.340295 | 0.242846 | 0.058974 |
| DRF_1_AutoML_7_20211207_112208 | 0.70194 | 0.236007 | 0.136992 | 0.373607 | 0.246723 | 0.0608724 |
| GBM_2_AutoML_7_20211207_112208 | 0.699097 | 0.236575 | 0.150062 | 0.361349 | 0.247184 | 0.0611 |
| XRT_1_AutoML_7_20211207_112208 | 0.697434 | 0.231245 | 0.134296 | 0.387849 | 0.245994 | 0.0605131 |
| GBM_5_AutoML_7_20211207_112208 | 0.693149 | 0.241952 | 0.14272 | 0.370965 | 0.251939 | 0.0634734 |
| GBM_grid_1_AutoML_7_20211207_112208_model_1 | 0.684286 | 0.236247 | 0.151177 | 0.361349 | 0.245974 | 0.0605031 |
| StackedEnsemble_BestOfFamily_4_AutoML_7_20211207_112208 | 0.674825 | 0.242088 | 0.146392 | 0.350206 | 0.250094 | 0.0625469 |
| StackedEnsemble_AllModels_4_AutoML_7_20211207_112208 | 0.654523 | 0.249973 | 0.1249 | 0.416399 | 0.251867 | 0.0634371 |
| GLM_1_AutoML_7_20211207_112208 | 0.60592 | 0.253441 | 0.10332 | 0.445929 | 0.249652 | 0.0623259 |
| DeepLearning_1_AutoML_7_20211207_112208 | 0.596019 | 0.389855 | 0.124748 | 0.409883 | 0.268022 | 0.0718357 |
model_ids = list(aml.leaderboard['model_id'].as_data_frame().iloc[:,0])
se = h2o.get_model([mid for mid in model_ids if "StackedEnsemble_AllModels" in mid][0])
metalearner = se.metalearner()
metalearner.coef_norm()
%matplotlib inline
metalearner.std_coef_plot()
y = "C591"
splits = df.split_frame(ratios = [0.8], seed = 1)
train = splits[0]
test = splits[1]
aml = H2OAutoML(max_runtime_secs = 60, seed = 1, project_name = "SMP")
aml.train(y = y, training_frame = train, leaderboard_frame = test)
AutoML progress: |█ 11:46:10.772: AutoML: XGBoost is not available; skipping it. 11:46:10.772: Step 'best_of_family_xgboost' not defined in provider 'StackedEnsemble': skipping it. 11:46:10.772: Step 'all_xgboost' not defined in provider 'StackedEnsemble': skipping it. ██████████████████████████████████████████████████████████████| (done) 100% Model Details ============= H2OStackedEnsembleEstimator : Stacked Ensemble Model Key: StackedEnsemble_AllModels_1_AutoML_8_20211207_114610 No model summary for this model ModelMetricsBinomialGLM: stackedensemble ** Reported on train data. ** MSE: 0.033851155031245465 RMSE: 0.1839868338529838 LogLoss: 0.12671535187943414 Null degrees of freedom: 1252 Residual degrees of freedom: 1250 Null deviance: 584.1880335470614 Residual deviance: 317.54867180986196 AIC: 323.54867180986196 AUC: 0.9888543371522095 AUCPR: 0.8787210051353 Gini: 0.977708674304419 Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.20880811549468148:
| -1 | 1 | Error | Rate | ||
|---|---|---|---|---|---|
| 0 | -1 | 1162.0 | 13.0 | 0.0111 | (13.0/1175.0) |
| 1 | 1 | 17.0 | 61.0 | 0.2179 | (17.0/78.0) |
| 2 | Total | 1179.0 | 74.0 | 0.0239 | (30.0/1253.0) |
Maximum Metrics: Maximum metrics at their respective thresholds
| metric | threshold | value | idx | |
|---|---|---|---|---|
| 0 | max f1 | 0.208808 | 0.802632 | 69.0 |
| 1 | max f2 | 0.144669 | 0.844749 | 109.0 |
| 2 | max f0point5 | 0.272960 | 0.833333 | 46.0 |
| 3 | max accuracy | 0.230326 | 0.976057 | 62.0 |
| 4 | max precision | 0.664540 | 1.000000 | 0.0 |
| 5 | max recall | 0.087132 | 1.000000 | 175.0 |
| 6 | max specificity | 0.664540 | 1.000000 | 0.0 |
| 7 | max absolute_mcc | 0.208808 | 0.790207 | 69.0 |
| 8 | max min_per_class_accuracy | 0.136155 | 0.948936 | 116.0 |
| 9 | max mean_per_class_accuracy | 0.136155 | 0.955237 | 116.0 |
| 10 | max tns | 0.664540 | 1175.000000 | 0.0 |
| 11 | max fns | 0.664540 | 77.000000 | 0.0 |
| 12 | max fps | 0.009425 | 1175.000000 | 399.0 |
| 13 | max tps | 0.087132 | 78.000000 | 175.0 |
| 14 | max tnr | 0.664540 | 1.000000 | 0.0 |
| 15 | max fnr | 0.664540 | 0.987179 | 0.0 |
| 16 | max fpr | 0.009425 | 1.000000 | 399.0 |
| 17 | max tpr | 0.087132 | 1.000000 | 175.0 |
Gains/Lift Table: Avg response rate: 6.23 %, avg score: 6.78 %
| group | cumulative_data_fraction | lower_threshold | lift | cumulative_lift | response_rate | score | cumulative_response_rate | cumulative_score | capture_rate | cumulative_capture_rate | gain | cumulative_gain | kolmogorov_smirnov | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 0.010375 | 0.468073 | 16.064103 | 16.064103 | 1.000000 | 0.538318 | 1.000000 | 0.538318 | 0.166667 | 0.166667 | 1506.410256 | 1506.410256 | 0.166667 |
| 1 | 2 | 0.019952 | 0.409661 | 16.064103 | 16.064103 | 1.000000 | 0.439704 | 1.000000 | 0.490983 | 0.153846 | 0.320513 | 1506.410256 | 1506.410256 | 0.320513 |
| 2 | 3 | 0.029529 | 0.301196 | 13.386752 | 15.195773 | 0.833333 | 0.351571 | 0.945946 | 0.445768 | 0.128205 | 0.448718 | 1238.675214 | 1419.577270 | 0.447016 |
| 3 | 4 | 0.039904 | 0.265268 | 13.592702 | 14.778974 | 0.846154 | 0.284495 | 0.920000 | 0.403837 | 0.141026 | 0.589744 | 1259.270217 | 1377.897436 | 0.586339 |
| 4 | 5 | 0.049481 | 0.238977 | 10.709402 | 13.991315 | 0.666667 | 0.252127 | 0.870968 | 0.374474 | 0.102564 | 0.692308 | 970.940171 | 1299.131514 | 0.685499 |
| 5 | 6 | 0.099761 | 0.145168 | 4.844729 | 9.381436 | 0.301587 | 0.178909 | 0.584000 | 0.275909 | 0.243590 | 0.935897 | 384.472934 | 838.143590 | 0.891642 |
| 6 | 7 | 0.149242 | 0.103740 | 1.036394 | 6.614630 | 0.064516 | 0.120620 | 0.411765 | 0.224423 | 0.051282 | 0.987179 | 3.639371 | 561.463047 | 0.893562 |
| 7 | 8 | 0.199521 | 0.083269 | 0.254986 | 5.012000 | 0.015873 | 0.092403 | 0.312000 | 0.191154 | 0.012821 | 1.000000 | -74.501425 | 401.200000 | 0.853617 |
| 8 | 9 | 0.299282 | 0.058937 | 0.000000 | 3.341333 | 0.000000 | 0.070182 | 0.208000 | 0.150830 | 0.000000 | 1.000000 | -100.000000 | 234.133333 | 0.747234 |
| 9 | 10 | 0.399840 | 0.047381 | 0.000000 | 2.500998 | 0.000000 | 0.052419 | 0.155689 | 0.126080 | 0.000000 | 1.000000 | -100.000000 | 150.099800 | 0.640000 |
| 10 | 11 | 0.499601 | 0.039860 | 0.000000 | 2.001597 | 0.000000 | 0.043316 | 0.124601 | 0.109554 | 0.000000 | 1.000000 | -100.000000 | 100.159744 | 0.533617 |
| 11 | 12 | 0.599362 | 0.033720 | 0.000000 | 1.668442 | 0.000000 | 0.036673 | 0.103862 | 0.097423 | 0.000000 | 1.000000 | -100.000000 | 66.844208 | 0.427234 |
| 12 | 13 | 0.699920 | 0.028689 | 0.000000 | 1.428734 | 0.000000 | 0.031241 | 0.088940 | 0.087915 | 0.000000 | 1.000000 | -100.000000 | 42.873432 | 0.320000 |
| 13 | 14 | 0.799681 | 0.023685 | 0.000000 | 1.250499 | 0.000000 | 0.026043 | 0.077844 | 0.080196 | 0.000000 | 1.000000 | -100.000000 | 25.049900 | 0.213617 |
| 14 | 15 | 0.899441 | 0.018469 | 0.000000 | 1.111801 | 0.000000 | 0.021154 | 0.069210 | 0.073647 | 0.000000 | 1.000000 | -100.000000 | 11.180124 | 0.107234 |
| 15 | 16 | 1.000000 | 0.009425 | 0.000000 | 1.000000 | 0.000000 | 0.015563 | 0.062251 | 0.067807 | 0.000000 | 1.000000 | -100.000000 | 0.000000 | 0.000000 |
ModelMetricsBinomialGLM: stackedensemble ** Reported on cross-validation data. ** MSE: 0.05605872445707176 RMSE: 0.2367672368742596 LogLoss: 0.21539553952302937 Null degrees of freedom: 1252 Residual degrees of freedom: 1249 Null deviance: 586.0139541700968 Residual deviance: 539.7812220447116 AIC: 547.7812220447116 AUC: 0.7153573376977632 AUCPR: 0.1571770784621038 Gini: 0.43071467539552644 Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.11070719266724438:
| -1 | 1 | Error | Rate | ||
|---|---|---|---|---|---|
| 0 | -1 | 1040.0 | 135.0 | 0.1149 | (135.0/1175.0) |
| 1 | 1 | 48.0 | 30.0 | 0.6154 | (48.0/78.0) |
| 2 | Total | 1088.0 | 165.0 | 0.146 | (183.0/1253.0) |
Maximum Metrics: Maximum metrics at their respective thresholds
| metric | threshold | value | idx | |
|---|---|---|---|---|
| 0 | max f1 | 0.110707 | 0.246914 | 121.0 |
| 1 | max f2 | 0.058870 | 0.356662 | 224.0 |
| 2 | max f0point5 | 0.130201 | 0.219780 | 95.0 |
| 3 | max accuracy | 0.487593 | 0.938547 | 0.0 |
| 4 | max precision | 0.487593 | 1.000000 | 0.0 |
| 5 | max recall | 0.019145 | 1.000000 | 368.0 |
| 6 | max specificity | 0.487593 | 1.000000 | 0.0 |
| 7 | max absolute_mcc | 0.110707 | 0.192720 | 121.0 |
| 8 | max min_per_class_accuracy | 0.058870 | 0.678298 | 224.0 |
| 9 | max mean_per_class_accuracy | 0.058870 | 0.678893 | 224.0 |
| 10 | max tns | 0.487593 | 1175.000000 | 0.0 |
| 11 | max fns | 0.487593 | 77.000000 | 0.0 |
| 12 | max fps | 0.006373 | 1175.000000 | 399.0 |
| 13 | max tps | 0.019145 | 78.000000 | 368.0 |
| 14 | max tnr | 0.487593 | 1.000000 | 0.0 |
| 15 | max fnr | 0.487593 | 0.987179 | 0.0 |
| 16 | max fpr | 0.006373 | 1.000000 | 399.0 |
| 17 | max tpr | 0.019145 | 1.000000 | 368.0 |
Gains/Lift Table: Avg response rate: 6.23 %, avg score: 6.20 %
| group | cumulative_data_fraction | lower_threshold | lift | cumulative_lift | response_rate | score | cumulative_response_rate | cumulative_score | capture_rate | cumulative_capture_rate | gain | cumulative_gain | kolmogorov_smirnov | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 0.009577 | 0.312778 | 5.354701 | 5.354701 | 0.333333 | 0.367853 | 0.333333 | 0.367853 | 0.051282 | 0.051282 | 435.470085 | 435.470085 | 0.044474 |
| 1 | 2 | 0.019952 | 0.249280 | 2.471400 | 3.855385 | 0.153846 | 0.274151 | 0.240000 | 0.319128 | 0.025641 | 0.076923 | 147.140039 | 285.538462 | 0.060753 |
| 2 | 3 | 0.029529 | 0.219262 | 2.677350 | 3.473319 | 0.166667 | 0.234171 | 0.216216 | 0.291574 | 0.025641 | 0.102564 | 167.735043 | 247.331947 | 0.077883 |
| 3 | 4 | 0.039904 | 0.197417 | 1.235700 | 2.891538 | 0.076923 | 0.207739 | 0.180000 | 0.269777 | 0.012821 | 0.115385 | 23.570020 | 189.153846 | 0.080491 |
| 4 | 5 | 0.049481 | 0.176818 | 4.016026 | 3.109181 | 0.250000 | 0.186907 | 0.193548 | 0.253738 | 0.038462 | 0.153846 | 301.602564 | 210.918114 | 0.111293 |
| 5 | 6 | 0.099761 | 0.127508 | 3.059829 | 3.084308 | 0.190476 | 0.147272 | 0.192000 | 0.200079 | 0.153846 | 0.307692 | 205.982906 | 208.430769 | 0.221735 |
| 6 | 7 | 0.149242 | 0.102488 | 1.813689 | 2.663033 | 0.112903 | 0.113378 | 0.165775 | 0.171333 | 0.089744 | 0.397436 | 81.368900 | 166.303305 | 0.264670 |
| 7 | 8 | 0.199521 | 0.087173 | 1.019943 | 2.248974 | 0.063492 | 0.094015 | 0.140000 | 0.151849 | 0.051282 | 0.448718 | 1.994302 | 124.897436 | 0.265739 |
| 8 | 9 | 0.299282 | 0.064863 | 1.285128 | 1.927692 | 0.080000 | 0.075005 | 0.120000 | 0.126235 | 0.128205 | 0.576923 | 28.512821 | 92.769231 | 0.296072 |
| 9 | 10 | 0.399840 | 0.050768 | 1.402422 | 1.795588 | 0.087302 | 0.057694 | 0.111776 | 0.108997 | 0.141026 | 0.717949 | 40.242165 | 79.558831 | 0.339225 |
| 10 | 11 | 0.499601 | 0.042069 | 0.257026 | 1.488367 | 0.016000 | 0.046284 | 0.092652 | 0.096474 | 0.025641 | 0.743590 | -74.297436 | 48.836733 | 0.260185 |
| 11 | 12 | 0.599362 | 0.035495 | 0.771077 | 1.368978 | 0.048000 | 0.038796 | 0.085220 | 0.086874 | 0.076923 | 0.820513 | -22.892308 | 36.897811 | 0.235832 |
| 12 | 13 | 0.699920 | 0.030476 | 0.764957 | 1.282197 | 0.047619 | 0.032885 | 0.079818 | 0.079117 | 0.076923 | 0.897436 | -23.504274 | 28.219747 | 0.210627 |
| 13 | 14 | 0.799681 | 0.024967 | 0.642564 | 1.202403 | 0.040000 | 0.027981 | 0.074850 | 0.072738 | 0.064103 | 0.961538 | -35.743590 | 20.240289 | 0.172602 |
| 14 | 15 | 0.899441 | 0.019699 | 0.257026 | 1.097547 | 0.016000 | 0.022397 | 0.068323 | 0.067154 | 0.025641 | 0.987179 | -74.297436 | 9.754738 | 0.093562 |
| 15 | 16 | 1.000000 | 0.006373 | 0.127493 | 1.000000 | 0.007937 | 0.016072 | 0.062251 | 0.062018 | 0.012821 | 1.000000 | -87.250712 | 0.000000 | 0.000000 |
aml2 = H2OAutoML(max_runtime_secs = 60, seed = 1, project_name = "SMP_FullData")
aml2.train(y = y, training_frame = df)
AutoML progress: |█ 11:49:04.472: AutoML: XGBoost is not available; skipping it. 11:49:04.475: Step 'best_of_family_xgboost' not defined in provider 'StackedEnsemble': skipping it. 11:49:04.475: Step 'all_xgboost' not defined in provider 'StackedEnsemble': skipping it. ██████████████████████████████████████████████████████████████| (done) 100% Model Details ============= H2OGradientBoostingEstimator : Gradient Boosting Machine Model Key: GBM_1_AutoML_9_20211207_114904 Model Summary:
| number_of_trees | number_of_internal_trees | model_size_in_bytes | min_depth | max_depth | mean_depth | min_leaves | max_leaves | mean_leaves | ||
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 26.0 | 26.0 | 4629.0 | 5.0 | 8.0 | 6.269231 | 7.0 | 10.0 | 9.5 |
ModelMetricsBinomial: gbm ** Reported on train data. ** MSE: 0.04228261959805645 RMSE: 0.2056273804678172 LogLoss: 0.1490274918993215 Mean Per-Class Error: 0.056801750880698276 AUC: 0.9807462274567538 AUCPR: 0.8002128146571157 Gini: 0.9614924549135075 Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.1873516146187685:
| -1 | 1 | Error | Rate | ||
|---|---|---|---|---|---|
| 0 | -1 | 1428.0 | 35.0 | 0.0239 | (35.0/1463.0) |
| 1 | 1 | 21.0 | 83.0 | 0.2019 | (21.0/104.0) |
| 2 | Total | 1449.0 | 118.0 | 0.0357 | (56.0/1567.0) |
Maximum Metrics: Maximum metrics at their respective thresholds
| metric | threshold | value | idx | |
|---|---|---|---|---|
| 0 | max f1 | 0.187352 | 0.747748 | 90.0 |
| 1 | max f2 | 0.128312 | 0.794165 | 141.0 |
| 2 | max f0point5 | 0.218215 | 0.782710 | 66.0 |
| 3 | max accuracy | 0.213605 | 0.968092 | 69.0 |
| 4 | max precision | 0.467031 | 1.000000 | 0.0 |
| 5 | max recall | 0.072925 | 1.000000 | 216.0 |
| 6 | max specificity | 0.467031 | 1.000000 | 0.0 |
| 7 | max absolute_mcc | 0.187352 | 0.730282 | 90.0 |
| 8 | max min_per_class_accuracy | 0.130455 | 0.932331 | 139.0 |
| 9 | max mean_per_class_accuracy | 0.116789 | 0.943198 | 153.0 |
| 10 | max tns | 0.467031 | 1463.000000 | 0.0 |
| 11 | max fns | 0.467031 | 103.000000 | 0.0 |
| 12 | max fps | 0.008006 | 1463.000000 | 399.0 |
| 13 | max tps | 0.072925 | 104.000000 | 216.0 |
| 14 | max tnr | 0.467031 | 1.000000 | 0.0 |
| 15 | max fnr | 0.467031 | 0.990385 | 0.0 |
| 16 | max fpr | 0.008006 | 1.000000 | 399.0 |
| 17 | max tpr | 0.072925 | 1.000000 | 216.0 |
Gains/Lift Table: Avg response rate: 6.64 %, avg score: 6.71 %
| group | cumulative_data_fraction | lower_threshold | lift | cumulative_lift | response_rate | score | cumulative_response_rate | cumulative_score | capture_rate | cumulative_capture_rate | gain | cumulative_gain | kolmogorov_smirnov | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 0.010211 | 0.345958 | 15.067308 | 15.067308 | 1.000000 | 0.391266 | 1.000000 | 0.391266 | 0.153846 | 0.153846 | 1406.730769 | 1406.730769 | 0.153846 |
| 1 | 2 | 0.020421 | 0.301403 | 10.358774 | 12.713041 | 0.687500 | 0.318404 | 0.843750 | 0.354835 | 0.105769 | 0.259615 | 935.877404 | 1171.304087 | 0.256198 |
| 2 | 3 | 0.030632 | 0.266930 | 14.125601 | 13.183894 | 0.937500 | 0.281384 | 0.875000 | 0.330351 | 0.144231 | 0.403846 | 1312.560096 | 1218.389423 | 0.399745 |
| 3 | 4 | 0.040204 | 0.239354 | 12.053846 | 12.914835 | 0.800000 | 0.251887 | 0.857143 | 0.311669 | 0.115385 | 0.519231 | 1105.384615 | 1191.483516 | 0.513079 |
| 4 | 5 | 0.050415 | 0.220284 | 10.358774 | 12.397152 | 0.687500 | 0.228355 | 0.822785 | 0.294796 | 0.105769 | 0.625000 | 935.877404 | 1139.715190 | 0.615431 |
| 5 | 6 | 0.100191 | 0.152900 | 4.636095 | 8.541340 | 0.307692 | 0.186622 | 0.566879 | 0.241053 | 0.230769 | 0.855769 | 363.609467 | 754.134003 | 0.809289 |
| 6 | 7 | 0.150606 | 0.113596 | 2.288705 | 6.448297 | 0.151899 | 0.130687 | 0.427966 | 0.204109 | 0.115385 | 0.971154 | 128.870497 | 544.829694 | 0.878878 |
| 7 | 8 | 0.200383 | 0.089771 | 0.193171 | 4.894476 | 0.012821 | 0.100963 | 0.324841 | 0.178487 | 0.009615 | 0.980769 | -80.682939 | 389.447575 | 0.835862 |
| 8 | 9 | 0.300574 | 0.063143 | 0.191940 | 3.326964 | 0.012739 | 0.073696 | 0.220807 | 0.143556 | 0.019231 | 1.000000 | -80.805977 | 232.696391 | 0.749146 |
| 9 | 10 | 0.400128 | 0.050895 | 0.000000 | 2.499203 | 0.000000 | 0.056864 | 0.165869 | 0.121987 | 0.000000 | 1.000000 | -100.000000 | 149.920255 | 0.642515 |
| 10 | 11 | 0.500319 | 0.041643 | 0.000000 | 1.998724 | 0.000000 | 0.046195 | 0.132653 | 0.106809 | 0.000000 | 1.000000 | -100.000000 | 99.872449 | 0.535202 |
| 11 | 12 | 0.600511 | 0.035315 | 0.000000 | 1.665250 | 0.000000 | 0.038341 | 0.110521 | 0.095386 | 0.000000 | 1.000000 | -100.000000 | 66.524973 | 0.427888 |
| 12 | 13 | 0.700064 | 0.029982 | 0.000000 | 1.428441 | 0.000000 | 0.032555 | 0.094804 | 0.086451 | 0.000000 | 1.000000 | -100.000000 | 42.844120 | 0.321258 |
| 13 | 14 | 0.800255 | 0.024996 | 0.000000 | 1.249601 | 0.000000 | 0.027576 | 0.082935 | 0.079080 | 0.000000 | 1.000000 | -100.000000 | 24.960128 | 0.213944 |
| 14 | 15 | 0.900447 | 0.019743 | 0.000000 | 1.110560 | 0.000000 | 0.022342 | 0.073707 | 0.072767 | 0.000000 | 1.000000 | -100.000000 | 11.055989 | 0.106630 |
| 15 | 16 | 1.000000 | 0.000000 | 0.000000 | 1.000000 | 0.000000 | 0.016195 | 0.066369 | 0.067135 | 0.000000 | 1.000000 | -100.000000 | 0.000000 | 0.000000 |
ModelMetricsBinomial: gbm ** Reported on cross-validation data. ** MSE: 0.05866704673851495 RMSE: 0.24221281291152819 LogLoss: 0.22188882828209225 Mean Per-Class Error: 0.30454085388295915 AUC: 0.7317287975182711 AUCPR: 0.17137421361920135 Gini: 0.46345759503654227 Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.08765627829832409:
| -1 | 1 | Error | Rate | ||
|---|---|---|---|---|---|
| 0 | -1 | 1205.0 | 258.0 | 0.1763 | (258.0/1463.0) |
| 1 | 1 | 50.0 | 54.0 | 0.4808 | (50.0/104.0) |
| 2 | Total | 1255.0 | 312.0 | 0.1966 | (308.0/1567.0) |
Maximum Metrics: Maximum metrics at their respective thresholds
| metric | threshold | value | idx | |
|---|---|---|---|---|
| 0 | max f1 | 0.087656 | 0.259615 | 179.0 |
| 1 | max f2 | 0.062379 | 0.386653 | 235.0 |
| 2 | max f0point5 | 0.185307 | 0.250000 | 68.0 |
| 3 | max accuracy | 0.401511 | 0.932993 | 0.0 |
| 4 | max precision | 0.351655 | 0.400000 | 3.0 |
| 5 | max recall | 0.020029 | 1.000000 | 373.0 |
| 6 | max specificity | 0.401511 | 0.999316 | 0.0 |
| 7 | max absolute_mcc | 0.087656 | 0.213739 | 179.0 |
| 8 | max min_per_class_accuracy | 0.062632 | 0.691729 | 234.0 |
| 9 | max mean_per_class_accuracy | 0.062379 | 0.695459 | 235.0 |
| 10 | max tns | 0.401511 | 1462.000000 | 0.0 |
| 11 | max fns | 0.401511 | 104.000000 | 0.0 |
| 12 | max fps | 0.008334 | 1463.000000 | 399.0 |
| 13 | max tps | 0.020029 | 104.000000 | 373.0 |
| 14 | max tnr | 0.401511 | 0.999316 | 0.0 |
| 15 | max fnr | 0.401511 | 1.000000 | 0.0 |
| 16 | max fpr | 0.008334 | 1.000000 | 399.0 |
| 17 | max tpr | 0.020029 | 1.000000 | 373.0 |
Gains/Lift Table: Avg response rate: 6.64 %, avg score: 6.47 %
| group | cumulative_data_fraction | lower_threshold | lift | cumulative_lift | response_rate | score | cumulative_response_rate | cumulative_score | capture_rate | cumulative_capture_rate | gain | cumulative_gain | kolmogorov_smirnov | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 0.009572 | 0.282464 | 3.013462 | 3.013462 | 0.200000 | 0.328772 | 0.200000 | 0.328772 | 0.028846 | 0.028846 | 201.346154 | 201.346154 | 0.020644 |
| 1 | 2 | 0.019783 | 0.247870 | 6.591947 | 4.860422 | 0.437500 | 0.265321 | 0.322581 | 0.296023 | 0.067308 | 0.096154 | 559.194712 | 386.042184 | 0.081800 |
| 2 | 3 | 0.029994 | 0.223362 | 1.883413 | 3.846972 | 0.125000 | 0.235879 | 0.255319 | 0.275548 | 0.019231 | 0.115385 | 88.341346 | 284.697218 | 0.091461 |
| 3 | 4 | 0.039566 | 0.200033 | 4.017949 | 3.888337 | 0.266667 | 0.208200 | 0.258065 | 0.259254 | 0.038462 | 0.153846 | 301.794872 | 288.833747 | 0.122404 |
| 4 | 5 | 0.049777 | 0.188790 | 2.825120 | 3.670242 | 0.187500 | 0.195634 | 0.243590 | 0.246204 | 0.028846 | 0.182692 | 182.512019 | 267.024162 | 0.142364 |
| 5 | 6 | 0.099553 | 0.137812 | 1.931706 | 2.800974 | 0.128205 | 0.160819 | 0.185897 | 0.203512 | 0.096154 | 0.278846 | 93.170611 | 180.097387 | 0.192038 |
| 6 | 7 | 0.149968 | 0.108901 | 2.670156 | 2.756997 | 0.177215 | 0.123020 | 0.182979 | 0.176453 | 0.134615 | 0.413462 | 167.015579 | 175.699673 | 0.282224 |
| 7 | 8 | 0.199745 | 0.087409 | 2.124877 | 2.599472 | 0.141026 | 0.098316 | 0.172524 | 0.156981 | 0.105769 | 0.519231 | 112.487673 | 159.947161 | 0.342197 |
| 8 | 9 | 0.299936 | 0.066531 | 1.055671 | 2.083777 | 0.070064 | 0.075580 | 0.138298 | 0.129790 | 0.105769 | 0.625000 | 5.567124 | 108.377660 | 0.348172 |
| 9 | 10 | 0.399489 | 0.055092 | 1.255609 | 1.877396 | 0.083333 | 0.060662 | 0.124601 | 0.112563 | 0.125000 | 0.750000 | 25.560897 | 87.739617 | 0.375427 |
| 10 | 11 | 0.499681 | 0.045706 | 0.479851 | 1.597173 | 0.031847 | 0.050275 | 0.106003 | 0.100073 | 0.048077 | 0.798077 | -52.014944 | 59.717310 | 0.319608 |
| 11 | 12 | 0.599872 | 0.037976 | 0.383880 | 1.394527 | 0.025478 | 0.041612 | 0.092553 | 0.090309 | 0.038462 | 0.836538 | -61.611955 | 39.452741 | 0.253490 |
| 12 | 13 | 0.699426 | 0.032390 | 0.579512 | 1.278522 | 0.038462 | 0.034898 | 0.084854 | 0.082422 | 0.057692 | 0.894231 | -42.048817 | 27.852155 | 0.208653 |
| 13 | 14 | 0.799617 | 0.026920 | 0.479851 | 1.178449 | 0.031847 | 0.029652 | 0.078212 | 0.075810 | 0.048077 | 0.942308 | -52.014944 | 17.844865 | 0.152834 |
| 14 | 15 | 0.899809 | 0.021123 | 0.479851 | 1.100661 | 0.031847 | 0.024237 | 0.073050 | 0.070068 | 0.048077 | 0.990385 | -52.014944 | 10.066148 | 0.097015 |
| 15 | 16 | 1.000000 | 0.008251 | 0.095970 | 1.000000 | 0.006369 | 0.016908 | 0.066369 | 0.064741 | 0.009615 | 1.000000 | -90.402989 | 0.000000 | 0.000000 |
Cross-Validation Metrics Summary:
| mean | sd | cv_1_valid | cv_2_valid | cv_3_valid | cv_4_valid | cv_5_valid | ||
|---|---|---|---|---|---|---|---|---|
| 0 | accuracy | 0.865265 | 0.079461 | 0.837061 | 0.939490 | 0.920382 | 0.888179 | 0.741214 |
| 1 | auc | 0.727110 | 0.034794 | 0.762519 | 0.686956 | 0.695353 | 0.733083 | 0.757641 |
| 2 | err | 0.134735 | 0.079461 | 0.162939 | 0.060510 | 0.079618 | 0.111821 | 0.258786 |
| 3 | err_count | 42.200000 | 24.843510 | 51.000000 | 19.000000 | 25.000000 | 35.000000 | 81.000000 |
| 4 | f0point5 | 0.288093 | 0.075562 | 0.259740 | 0.272727 | 0.421053 | 0.251799 | 0.235149 |
| 5 | f1 | 0.311057 | 0.055023 | 0.320000 | 0.240000 | 0.390244 | 0.285714 | 0.319328 |
| 6 | f2 | 0.364432 | 0.105025 | 0.416667 | 0.214286 | 0.363636 | 0.330189 | 0.497382 |
| 7 | lift_top_group | 4.856111 | 3.807497 | 3.402174 | 0.000000 | 10.239130 | 4.118421 | 6.520834 |
| 8 | logloss | 0.223798 | 0.024534 | 0.237960 | 0.187096 | 0.239604 | 0.210027 | 0.244305 |
| 9 | max_per_class_error | 0.564998 | 0.203715 | 0.478261 | 0.800000 | 0.652174 | 0.631579 | 0.262976 |
| 10 | mcc | 0.275246 | 0.054887 | 0.269064 | 0.214490 | 0.351328 | 0.235385 | 0.305961 |
| 11 | mean_per_class_accuracy | 0.669274 | 0.064904 | 0.691904 | 0.588294 | 0.656731 | 0.645095 | 0.764345 |
| 12 | mean_per_class_error | 0.330726 | 0.064904 | 0.308096 | 0.411706 | 0.343269 | 0.354905 | 0.235655 |
| 13 | mse | 0.058902 | 0.008471 | 0.064952 | 0.046062 | 0.062566 | 0.054668 | 0.066264 |
| 14 | pr_auc | 0.198647 | 0.073271 | 0.211031 | 0.098676 | 0.287013 | 0.156319 | 0.240197 |
| 15 | precision | 0.281709 | 0.098016 | 0.230769 | 0.300000 | 0.444444 | 0.233333 | 0.200000 |
| 16 | r2 | 0.043392 | 0.034619 | 0.045981 | -0.012604 | 0.078325 | 0.041212 | 0.064045 |
| 17 | recall | 0.445931 | 0.224385 | 0.521739 | 0.200000 | 0.347826 | 0.368421 | 0.791667 |
| 18 | rmse | 0.242168 | 0.017928 | 0.254857 | 0.214621 | 0.250132 | 0.233812 | 0.257417 |
| 19 | specificity | 0.892617 | 0.097948 | 0.862069 | 0.976589 | 0.965636 | 0.921769 | 0.737024 |
Scoring History:
| timestamp | duration | number_of_trees | training_rmse | training_logloss | training_auc | training_pr_auc | training_lift | training_classification_error | ||
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2021-12-07 11:49:45 | 15.984 sec | 0.0 | 0.248926 | 0.244143 | 0.500000 | 0.066369 | 1.000000 | 0.933631 | |
| 1 | 2021-12-07 11:49:46 | 16.631 sec | 5.0 | 0.241325 | 0.217910 | 0.890126 | 0.316637 | 6.696581 | 0.147415 | |
| 2 | 2021-12-07 11:49:47 | 17.327 sec | 10.0 | 0.234679 | 0.199680 | 0.911375 | 0.370801 | 9.417067 | 0.149968 | |
| 3 | 2021-12-07 11:49:47 | 18.011 sec | 15.0 | 0.226149 | 0.181541 | 0.938627 | 0.499929 | 12.242188 | 0.074027 | |
| 4 | 2021-12-07 11:49:48 | 18.665 sec | 20.0 | 0.216793 | 0.165525 | 0.963780 | 0.635038 | 13.183894 | 0.059987 | |
| 5 | 2021-12-07 11:49:49 | 19.297 sec | 25.0 | 0.207021 | 0.151123 | 0.979451 | 0.788485 | 15.067308 | 0.037652 | |
| 6 | 2021-12-07 11:49:49 | 19.442 sec | 26.0 | 0.205627 | 0.149027 | 0.980746 | 0.800213 | 15.067308 | 0.035737 |
Variable Importances:
| variable | relative_importance | scaled_importance | percentage | |
|---|---|---|---|---|
| 0 | C60 | 20.094303 | 1.000000 | 0.192170 |
| 1 | C66 | 5.754906 | 0.286395 | 0.055036 |
| 2 | C22 | 4.097161 | 0.203897 | 0.039183 |
| 3 | C206 | 2.994663 | 0.149030 | 0.028639 |
| 4 | C511 | 2.409086 | 0.119889 | 0.023039 |
| 5 | C82 | 2.274860 | 0.113209 | 0.021755 |
| 6 | C424 | 2.054876 | 0.102262 | 0.019652 |
| 7 | C49 | 1.957563 | 0.097419 | 0.018721 |
| 8 | C320 | 1.945023 | 0.096795 | 0.018601 |
| 9 | C130 | 1.735883 | 0.086387 | 0.016601 |
| 10 | C337 | 1.650771 | 0.082151 | 0.015787 |
| 11 | C426 | 1.452263 | 0.072272 | 0.013889 |
| 12 | C347 | 1.431513 | 0.071240 | 0.013690 |
| 13 | C489 | 1.414950 | 0.070415 | 0.013532 |
| 14 | C541 | 1.397532 | 0.069549 | 0.013365 |
| 15 | C478 | 1.285023 | 0.063950 | 0.012289 |
| 16 | C318 | 1.143859 | 0.056925 | 0.010939 |
| 17 | C256 | 1.139171 | 0.056691 | 0.010894 |
| 18 | C77 | 1.130548 | 0.056262 | 0.010812 |
| 19 | C34 | 1.101779 | 0.054830 | 0.010537 |
See the whole table with table.as_data_frame()
aml.leaderboard.head()
| model_id | auc | logloss | aucpr | mean_per_class_error | rmse | mse |
|---|---|---|---|---|---|---|
| StackedEnsemble_AllModels_1_AutoML_8_20211207_114610 | 0.736245 | 0.260767 | 0.216197 | 0.344151 | 0.267765 | 0.0716978 |
| GBM_1_AutoML_8_20211207_114610 | 0.731571 | 0.264252 | 0.199682 | 0.363381 | 0.269478 | 0.0726182 |
| StackedEnsemble_BestOfFamily_1_AutoML_8_20211207_114610 | 0.731571 | 0.263063 | 0.199682 | 0.363381 | 0.269091 | 0.07241 |
| StackedEnsemble_BestOfFamily_2_AutoML_8_20211207_114610 | 0.731303 | 0.263074 | 0.199629 | 0.363381 | 0.26909 | 0.0724096 |
| GLM_1_AutoML_8_20211207_114610 | 0.674947 | 0.287462 | 0.159559 | 0.394899 | 0.276067 | 0.0762131 |
| GBM_3_AutoML_8_20211207_114610 | 0.654581 | 0.273623 | 0.178792 | 0.347623 | 0.272074 | 0.0740243 |
| GBM_2_AutoML_8_20211207_114610 | 0.65191 | 0.277717 | 0.137756 | 0.325988 | 0.273766 | 0.0749481 |
| GBM_4_AutoML_8_20211207_114610 | 0.565505 | 0.285846 | 0.107072 | 0.371261 | 0.276223 | 0.0762992 |
| DRF_1_AutoML_8_20211207_114610 | 0.505609 | 1.75511 | 0.0978362 | 0.5 | 0.319899 | 0.102335 |
aml2.leaderboard.head()
| model_id | auc | logloss | aucpr | mean_per_class_error | rmse | mse |
|---|---|---|---|---|---|---|
| GBM_1_AutoML_9_20211207_114904 | 0.731729 | 0.221889 | 0.171374 | 0.32856 | 0.242213 | 0.058667 |
| StackedEnsemble_AllModels_1_AutoML_9_20211207_114904 | 0.725022 | 0.223956 | 0.165368 | 0.340022 | 0.243647 | 0.0593638 |
| StackedEnsemble_BestOfFamily_1_AutoML_9_20211207_114904 | 0.72071 | 0.223738 | 0.162217 | 0.340295 | 0.242846 | 0.058974 |
| StackedEnsemble_BestOfFamily_2_AutoML_9_20211207_114904 | 0.719649 | 0.223785 | 0.163549 | 0.349272 | 0.242811 | 0.0589571 |
| GBM_2_AutoML_9_20211207_114904 | 0.684464 | 0.230814 | 0.161693 | 0.342276 | 0.244648 | 0.0598525 |
| GBM_3_AutoML_9_20211207_114904 | 0.638634 | 0.234052 | 0.131686 | 0.357748 | 0.245966 | 0.0604992 |
| GLM_1_AutoML_9_20211207_114904 | 0.60592 | 0.253441 | 0.10332 | 0.445929 | 0.249652 | 0.0623259 |
| GBM_4_AutoML_9_20211207_114904 | 0.603567 | 0.239495 | 0.100628 | 0.370735 | 0.247825 | 0.061417 |
| DRF_1_AutoML_9_20211207_114904 | 0.563276 | 1.28183 | 0.0878796 | 0.425716 | 0.280054 | 0.0784302 |
pred = aml.predict(test)
pred.head()
stackedensemble prediction progress: |███████████████████████████████████████████| (done) 100%
| predict | p-1 | p1 |
|---|---|---|
| -1 | 0.958551 | 0.0414492 |
| 1 | 0.774607 | 0.225393 |
| 1 | 0.748403 | 0.251597 |
| 1 | 0.796802 | 0.203198 |
| 1 | 0.677413 | 0.322587 |
| -1 | 0.916956 | 0.083044 |
| 1 | 0.569527 | 0.430473 |
| -1 | 0.946438 | 0.0535615 |
| -1 | 0.941466 | 0.0585339 |
| 1 | 0.857636 | 0.142364 |
perf = aml.leader.model_performance(test)
perf
ModelMetricsBinomialGLM: stackedensemble ** Reported on test data. ** MSE: 0.07169783210918163 RMSE: 0.26776450868100804 LogLoss: 0.26076718023235734 Null degrees of freedom: 313 Residual degrees of freedom: 311 Null deviance: 181.40350697779476 Residual deviance: 163.7617891859204 AIC: 169.7617891859204 AUC: 0.7362446581196581 AUCPR: 0.21619697998357104 Gini: 0.4724893162393162 Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.11327672772062818:
| -1 | 1 | Error | Rate | ||
|---|---|---|---|---|---|
| 0 | -1 | 267.0 | 21.0 | 0.0729 | (21.0/288.0) |
| 1 | 1 | 16.0 | 10.0 | 0.6154 | (16.0/26.0) |
| 2 | Total | 283.0 | 31.0 | 0.1178 | (37.0/314.0) |
Maximum Metrics: Maximum metrics at their respective thresholds
| metric | threshold | value | idx | |
|---|---|---|---|---|
| 0 | max f1 | 0.113277 | 0.350877 | 30.0 |
| 1 | max f2 | 0.079220 | 0.433526 | 68.0 |
| 2 | max f0point5 | 0.113277 | 0.333333 | 30.0 |
| 3 | max accuracy | 0.276783 | 0.917197 | 5.0 |
| 4 | max precision | 0.276783 | 0.500000 | 5.0 |
| 5 | max recall | 0.020453 | 1.000000 | 278.0 |
| 6 | max specificity | 0.430473 | 0.996528 | 0.0 |
| 7 | max absolute_mcc | 0.113277 | 0.287968 | 30.0 |
| 8 | max min_per_class_accuracy | 0.065224 | 0.653846 | 96.0 |
| 9 | max mean_per_class_accuracy | 0.079220 | 0.694712 | 68.0 |
| 10 | max tns | 0.430473 | 287.000000 | 0.0 |
| 11 | max fns | 0.430473 | 26.000000 | 0.0 |
| 12 | max fps | 0.009215 | 288.000000 | 313.0 |
| 13 | max tps | 0.020453 | 26.000000 | 278.0 |
| 14 | max tnr | 0.430473 | 0.996528 | 0.0 |
| 15 | max fnr | 0.430473 | 1.000000 | 0.0 |
| 16 | max fpr | 0.009215 | 1.000000 | 313.0 |
| 17 | max tpr | 0.020453 | 1.000000 | 278.0 |
Gains/Lift Table: Avg response rate: 8.28 %, avg score: 6.25 %
| group | cumulative_data_fraction | lower_threshold | lift | cumulative_lift | response_rate | score | cumulative_response_rate | cumulative_score | capture_rate | cumulative_capture_rate | gain | cumulative_gain | kolmogorov_smirnov | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 0.012739 | 0.318385 | 3.019231 | 3.019231 | 0.250000 | 0.378223 | 0.250000 | 0.378223 | 0.038462 | 0.038462 | 201.923077 | 201.923077 | 0.028045 |
| 1 | 2 | 0.022293 | 0.269145 | 8.051282 | 5.175824 | 0.666667 | 0.280784 | 0.428571 | 0.336463 | 0.076923 | 0.115385 | 705.128205 | 417.582418 | 0.101496 |
| 2 | 3 | 0.031847 | 0.212662 | 0.000000 | 3.623077 | 0.000000 | 0.229915 | 0.300000 | 0.304499 | 0.000000 | 0.115385 | -100.000000 | 262.307692 | 0.091079 |
| 3 | 4 | 0.041401 | 0.198191 | 4.025641 | 3.715976 | 0.333333 | 0.209110 | 0.307692 | 0.282486 | 0.038462 | 0.153846 | 302.564103 | 271.597633 | 0.122596 |
| 4 | 5 | 0.050955 | 0.183657 | 4.025641 | 3.774038 | 0.333333 | 0.191200 | 0.312500 | 0.265370 | 0.038462 | 0.192308 | 302.564103 | 277.403846 | 0.154113 |
| 5 | 6 | 0.101911 | 0.111564 | 3.774038 | 3.774038 | 0.312500 | 0.136782 | 0.312500 | 0.201076 | 0.192308 | 0.384615 | 277.403846 | 277.403846 | 0.308226 |
| 6 | 7 | 0.149682 | 0.097495 | 0.805128 | 2.826514 | 0.066667 | 0.103189 | 0.234043 | 0.169836 | 0.038462 | 0.423077 | -19.487179 | 182.651391 | 0.298077 |
| 7 | 8 | 0.200637 | 0.082390 | 1.509615 | 2.492063 | 0.125000 | 0.088910 | 0.206349 | 0.149283 | 0.076923 | 0.500000 | 50.961538 | 149.206349 | 0.326389 |
| 8 | 9 | 0.299363 | 0.066037 | 1.168734 | 2.055646 | 0.096774 | 0.073385 | 0.170213 | 0.124253 | 0.115385 | 0.615385 | 16.873449 | 105.564648 | 0.344551 |
| 9 | 10 | 0.401274 | 0.054721 | 0.377404 | 1.629426 | 0.031250 | 0.060614 | 0.134921 | 0.108091 | 0.038462 | 0.653846 | -62.259615 | 62.942613 | 0.275374 |
| 10 | 11 | 0.500000 | 0.045818 | 1.168734 | 1.538462 | 0.096774 | 0.049337 | 0.127389 | 0.096490 | 0.115385 | 0.769231 | 16.873449 | 53.846154 | 0.293536 |
| 11 | 12 | 0.598726 | 0.038054 | 0.779156 | 1.413257 | 0.064516 | 0.042010 | 0.117021 | 0.087506 | 0.076923 | 0.846154 | -22.084367 | 41.325696 | 0.269765 |
| 12 | 13 | 0.700637 | 0.031868 | 0.377404 | 1.262587 | 0.031250 | 0.035111 | 0.104545 | 0.079885 | 0.038462 | 0.884615 | -62.259615 | 26.258741 | 0.200588 |
| 13 | 14 | 0.799363 | 0.024105 | 0.389578 | 1.154766 | 0.032258 | 0.027300 | 0.095618 | 0.073391 | 0.038462 | 0.923077 | -61.042184 | 15.476555 | 0.134882 |
| 14 | 15 | 0.898089 | 0.019990 | 0.779156 | 1.113475 | 0.064516 | 0.021772 | 0.092199 | 0.067716 | 0.076923 | 1.000000 | -22.084367 | 11.347518 | 0.111111 |
| 15 | 16 | 1.000000 | 0.009215 | 0.000000 | 1.000000 | 0.000000 | 0.016242 | 0.082803 | 0.062471 | 0.000000 | 1.000000 | -100.000000 | 0.000000 | 0.000000 |
Future = pd.read_csv('Future_predictions.csv')
print(Future.shape)
Future.head()
(18, 591)
| Time | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ... | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 19-07-2008 11:55 | 3030.93 | 2564.00 | 2187.7333 | 1411.1265 | 1.3602 | 100 | 97.6133 | 0.1242 | 1.5005 | ... | 0.0000 | 0.0000 | 0.5005 | 0.0118 | 0.0035 | 2.3630 | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
| 1 | 19-07-2008 12:32 | 3095.78 | 2465.14 | 2230.4222 | 1463.6606 | 0.8294 | 100 | 102.3433 | 0.1247 | 1.4966 | ... | 0.0060 | 208.2045 | 0.5019 | 0.0223 | 0.0055 | 4.4447 | 0.0096 | 0.0201 | 0.0060 | 208.2045 |
| 2 | 19-07-2008 13:17 | 2932.61 | 2559.94 | 2186.4111 | 1698.0172 | 1.5102 | 100 | 95.4878 | 0.1241 | 1.4436 | ... | 0.0148 | 82.8602 | 0.4958 | 0.0157 | 0.0039 | 3.1745 | 0.0584 | 0.0484 | 0.0148 | 82.8602 |
| 3 | 19-07-2008 14:43 | 2988.72 | 2479.90 | 2199.0333 | 909.7926 | 1.3204 | 100 | 104.2367 | 0.1217 | 1.4882 | ... | 0.0044 | 73.8432 | 0.4990 | 0.0103 | 0.0025 | 2.0544 | 0.0202 | 0.0149 | 0.0044 | 73.8432 |
| 4 | 19-07-2008 15:22 | 3032.24 | 2502.87 | 2233.3667 | 1326.5200 | 1.5334 | 100 | 100.3967 | 0.1235 | 1.5031 | ... | 0.0000 | 0.0000 | 0.4800 | 0.4766 | 0.1045 | 99.3032 | 0.0202 | 0.0149 | 0.0044 | 73.8432 |
5 rows × 591 columns
import plotly.graph_objects as go
import plotly.express as px
Future = Future.replace(np.NaN, 0)
print(Future.isnull().sum())
Time 0
0 0
1 0
2 0
3 0
..
585 0
586 0
587 0
588 0
589 0
Length: 591, dtype: int64
Future.describe().T.style.bar(
subset=['mean'],
color='Reds').background_gradient(
subset=['std'], cmap='ocean').background_gradient(subset=['50%'], cmap='PuBu')
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| 0 | 18.000000 | 3000.383333 | 49.608715 | 2920.070000 | 2964.897500 | 3005.080000 | 3031.912500 | 3095.780000 |
| 1 | 18.000000 | 2526.248889 | 70.409195 | 2428.370000 | 2479.525000 | 2523.530000 | 2560.637500 | 2690.150000 |
| 2 | 18.000000 | 2222.672217 | 28.412225 | 2184.433300 | 2195.394425 | 2227.522200 | 2245.016675 | 2270.255600 |
| 3 | 18.000000 | 1200.046806 | 255.818978 | 877.626600 | 1004.469200 | 1152.301300 | 1389.974875 | 1698.017200 |
| 4 | 18.000000 | 1.208883 | 0.284415 | 0.788400 | 0.871025 | 1.320400 | 1.395000 | 1.533400 |
| 5 | 18.000000 | 100.000000 | 0.000000 | 100.000000 | 100.000000 | 100.000000 | 100.000000 | 100.000000 |
| 6 | 18.000000 | 102.962106 | 3.395897 | 95.487800 | 100.883350 | 103.788350 | 104.848900 | 107.871100 |
| 7 | 18.000000 | 0.122056 | 0.002388 | 0.118500 | 0.119950 | 0.122300 | 0.124075 | 0.125700 |
| 8 | 18.000000 | 1.508550 | 0.039830 | 1.436800 | 1.490300 | 1.514850 | 1.534600 | 1.581600 |
| 9 | 18.000000 | 0.003572 | 0.017393 | -0.027000 | -0.010075 | 0.012750 | 0.016125 | 0.025000 |
| 10 | 18.000000 | -0.001594 | 0.008882 | -0.015400 | -0.005875 | -0.002900 | 0.001300 | 0.021600 |
| 11 | 18.000000 | 0.955267 | 0.008500 | 0.943300 | 0.946150 | 0.958650 | 0.961575 | 0.969900 |
| 12 | 18.000000 | 201.648722 | 6.842171 | 192.978700 | 200.490750 | 201.980150 | 202.344475 | 226.008600 |
| 13 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 14 | 18.000000 | 10.437922 | 1.684240 | 7.955800 | 9.210225 | 9.884400 | 12.099525 | 13.687200 |
| 15 | 18.000000 | 417.363083 | 5.290284 | 408.401700 | 414.365625 | 416.296350 | 420.562525 | 428.982600 |
| 16 | 18.000000 | 9.738322 | 0.387699 | 9.199900 | 9.436200 | 9.698500 | 10.032225 | 10.410900 |
| 17 | 18.000000 | 0.967889 | 0.004664 | 0.951600 | 0.966850 | 0.968350 | 0.969275 | 0.974700 |
| 18 | 18.000000 | 191.910406 | 6.640586 | 183.386900 | 191.242800 | 192.052300 | 192.684150 | 215.597700 |
| 19 | 18.000000 | 12.388433 | 0.421946 | 10.702900 | 12.461150 | 12.476100 | 12.524475 | 12.540400 |
| 20 | 18.000000 | 1.404950 | 0.013688 | 1.382500 | 1.397950 | 1.404850 | 1.416950 | 1.427800 |
| 21 | 18.000000 | -5018.138889 | 1354.173579 | -6154.000000 | -5721.062500 | -5458.000000 | -5367.000000 | -1431.500000 |
| 22 | 18.000000 | 2471.305556 | 674.228625 | 619.500000 | 2562.000000 | 2662.000000 | 2845.687500 | 3417.750000 |
| 23 | 18.000000 | -3480.791667 | 903.081397 | -4515.000000 | -3965.375000 | -3876.625000 | -3528.437500 | -1025.250000 |
| 24 | 18.000000 | -250.902778 | 1138.079866 | -2445.000000 | -1414.437500 | 162.750000 | 612.125000 | 873.750000 |
| 25 | 18.000000 | 0.959333 | 0.340253 | 0.232800 | 0.893625 | 0.904400 | 1.295150 | 1.328000 |
| 26 | 18.000000 | 1.667467 | 0.468792 | 0.439000 | 1.770000 | 1.780100 | 2.000650 | 2.029500 |
| 27 | 18.000000 | 4.409944 | 2.521497 | 0.767200 | 3.038125 | 3.107650 | 7.304575 | 7.578800 |
| 28 | 18.000000 | 64.335794 | 2.741885 | 60.244400 | 62.575000 | 63.366700 | 67.108300 | 68.711100 |
| 29 | 18.000000 | 2.382711 | 0.381450 | 1.633300 | 2.169400 | 2.316650 | 2.605525 | 3.155600 |
| 30 | 18.000000 | 0.196739 | 0.030673 | 0.139400 | 0.176150 | 0.198400 | 0.209675 | 0.269600 |
| 31 | 18.000000 | 3.489156 | 0.084033 | 3.272800 | 3.459175 | 3.504800 | 3.521450 | 3.665100 |
| 32 | 18.000000 | 85.030650 | 0.951356 | 83.397100 | 84.756900 | 84.978500 | 85.426375 | 87.154300 |
| 33 | 18.000000 | 9.064589 | 0.420413 | 8.576200 | 8.691400 | 8.963000 | 9.434625 | 9.799700 |
| 34 | 18.000000 | 50.371394 | 0.186354 | 50.059500 | 50.189900 | 50.448500 | 50.504825 | 50.659600 |
| 35 | 18.000000 | 64.149456 | 0.151875 | 63.829400 | 64.096625 | 64.131800 | 64.240675 | 64.402100 |
| 36 | 18.000000 | 49.628617 | 0.186347 | 49.340400 | 49.495175 | 49.551550 | 49.810100 | 49.940500 |
| 37 | 18.000000 | 65.855422 | 0.587223 | 64.919300 | 65.195100 | 66.108350 | 66.327675 | 66.505000 |
| 38 | 18.000000 | 86.740378 | 0.946658 | 84.732700 | 86.447825 | 86.749300 | 87.009350 | 88.331200 |
| 39 | 18.000000 | 118.255900 | 1.757665 | 116.536000 | 117.137900 | 117.638200 | 118.523750 | 122.088600 |
| 40 | 18.000000 | 65.916111 | 19.880589 | 14.370000 | 61.147500 | 74.515000 | 76.900000 | 78.250000 |
| 41 | 18.000000 | 3.227389 | 1.281761 | 1.279000 | 2.324500 | 3.120500 | 3.951500 | 5.434000 |
| 42 | 18.000000 | 70.000000 | 0.000000 | 70.000000 | 70.000000 | 70.000000 | 70.000000 | 70.000000 |
| 43 | 18.000000 | 358.179394 | 5.020551 | 350.174500 | 352.872975 | 359.621850 | 361.997975 | 366.154500 |
| 44 | 18.000000 | 9.959256 | 0.202864 | 9.723500 | 9.793700 | 9.917950 | 10.055825 | 10.409100 |
| 45 | 18.000000 | 139.672172 | 11.478393 | 120.281800 | 132.552300 | 139.790000 | 142.599300 | 176.313600 |
| 46 | 18.000000 | 740.506083 | 16.651345 | 723.030900 | 726.725725 | 737.497550 | 746.693125 | 789.752300 |
| 47 | 18.000000 | 1.141200 | 0.153443 | 0.897400 | 0.976875 | 1.193100 | 1.260575 | 1.307200 |
| 48 | 18.000000 | 139.389994 | 3.023645 | 136.083600 | 137.266150 | 138.152700 | 140.843150 | 146.485500 |
| 49 | 18.000000 | 1.000000 | 0.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 50 | 18.000000 | 637.241556 | 10.886987 | 621.430000 | 630.275450 | 637.508150 | 640.137250 | 667.741800 |
| 51 | 18.000000 | 190.206028 | 45.206035 | 112.752400 | 152.852575 | 198.063900 | 217.976500 | 255.631000 |
| 52 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 53 | 18.000000 | 4.590944 | 0.056058 | 4.486000 | 4.563750 | 4.608000 | 4.636000 | 4.647000 |
| 54 | 18.000000 | 4.854056 | 0.068076 | 4.748000 | 4.814250 | 4.868000 | 4.915000 | 4.931000 |
| 55 | 18.000000 | 2875.166667 | 31.267818 | 2834.000000 | 2856.000000 | 2865.000000 | 2884.000000 | 2936.000000 |
| 56 | 18.000000 | 0.927006 | 0.006897 | 0.913900 | 0.923350 | 0.931600 | 0.931675 | 0.932400 |
| 57 | 18.000000 | 0.945811 | 0.004022 | 0.942500 | 0.943300 | 0.944450 | 0.947150 | 0.958600 |
| 58 | 18.000000 | 4.612578 | 0.052004 | 4.482800 | 4.587300 | 4.621950 | 4.627500 | 4.705700 |
| 59 | 18.000000 | 13.809850 | 14.968587 | -12.294500 | -0.692700 | 21.521800 | 26.505225 | 29.130900 |
| 60 | 18.000000 | 358.418494 | 5.352772 | 350.926400 | 352.345875 | 360.189550 | 362.942075 | 365.046400 |
| 61 | 18.000000 | 10.126717 | 0.313864 | 9.667500 | 9.835525 | 10.162350 | 10.353675 | 10.623100 |
| 62 | 18.000000 | 121.259800 | 9.489772 | 108.119100 | 114.749125 | 119.336350 | 129.500450 | 144.019100 |
| 63 | 18.000000 | 11.059100 | 4.154847 | 5.593600 | 8.108725 | 10.565450 | 12.715000 | 21.978200 |
| 64 | 18.000000 | 18.412372 | 6.017118 | 10.869100 | 13.494775 | 17.633200 | 21.592975 | 32.294500 |
| 65 | 18.000000 | 25.567272 | 7.412367 | 15.309400 | 20.381450 | 24.541700 | 28.011925 | 44.149800 |
| 66 | 18.000000 | 714.938828 | 14.263917 | 693.772400 | 704.799750 | 712.574350 | 727.037275 | 745.602500 |
| 67 | 18.000000 | 0.959961 | 0.078151 | 0.869200 | 0.911575 | 0.935700 | 0.992575 | 1.159800 |
| 68 | 18.000000 | 147.609500 | 3.522391 | 142.515500 | 144.621175 | 146.902250 | 150.183900 | 154.370900 |
| 69 | 18.000000 | 1.000000 | 0.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 70 | 18.000000 | 627.287767 | 10.565195 | 608.170000 | 619.602050 | 626.752250 | 635.602050 | 645.763600 |
| 71 | 18.000000 | 82.903950 | 17.276064 | 57.084100 | 70.264350 | 81.247850 | 90.316525 | 112.090400 |
| 72 | 18.000000 | 69.783144 | 80.490539 | 0.000000 | 0.000000 | 0.000000 | 156.424625 | 170.581500 |
| 73 | 18.000000 | 208.639083 | 240.066590 | 0.000000 | 0.000000 | 0.000000 | 467.260400 | 485.266500 |
| 74 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 75 | 18.000000 | -0.010433 | 0.020641 | -0.055500 | -0.017800 | -0.009700 | 0.001650 | 0.022700 |
| 76 | 18.000000 | -0.041656 | 0.026015 | -0.094700 | -0.055750 | -0.048350 | -0.021700 | 0.018300 |
| 77 | 18.000000 | -0.012333 | 0.027725 | -0.065000 | -0.028250 | -0.001550 | 0.004825 | 0.024900 |
| 78 | 18.000000 | -0.037344 | 0.082751 | -0.348200 | -0.044675 | -0.034400 | 0.005900 | 0.040000 |
| 79 | 18.000000 | 0.005017 | 0.031852 | -0.042300 | -0.007575 | 0.000000 | 0.008650 | 0.067600 |
| 80 | 18.000000 | -0.037811 | 0.058661 | -0.113400 | -0.085375 | -0.037600 | -0.001450 | 0.081900 |
| 81 | 18.000000 | -0.023550 | 0.018712 | -0.064600 | -0.035400 | -0.021650 | -0.012000 | 0.002800 |
| 82 | 18.000000 | 0.011356 | 0.031623 | -0.100300 | 0.001025 | 0.024050 | 0.028775 | 0.035600 |
| 83 | 18.000000 | 7.308333 | 0.562315 | 6.216600 | 6.879250 | 7.492900 | 7.582850 | 8.412600 |
| 84 | 18.000000 | 0.135078 | 0.004731 | 0.125300 | 0.132075 | 0.135250 | 0.136800 | 0.147900 |
| 85 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 86 | 18.000000 | 2.402406 | 0.050233 | 2.294400 | 2.367525 | 2.400050 | 2.453150 | 2.470400 |
| 87 | 18.000000 | 0.981283 | 0.010189 | 0.964200 | 0.969125 | 0.988150 | 0.989300 | 0.990600 |
| 88 | 18.000000 | 1773.365767 | 75.059770 | 1632.312000 | 1720.881125 | 1764.712450 | 1827.816225 | 1931.646400 |
| 89 | 18.000000 | 0.325056 | 0.402583 | 0.149700 | 0.172900 | 0.190450 | 0.203150 | 1.472700 |
| 90 | 18.000000 | 8714.982761 | 428.395594 | 7869.700000 | 8502.547475 | 8730.715100 | 9079.080000 | 9317.169800 |
| 91 | 18.000000 | -0.027594 | 0.115585 | -0.327400 | -0.091900 | -0.005000 | 0.044100 | 0.145500 |
| 92 | 18.000000 | -0.001100 | 0.003412 | -0.007700 | -0.002800 | -0.000900 | 0.000825 | 0.005200 |
| 93 | 18.000000 | -0.000883 | 0.001360 | -0.003300 | -0.001800 | -0.000850 | -0.000100 | 0.001800 |
| 94 | 18.000000 | -0.000067 | 0.000146 | -0.000500 | -0.000100 | -0.000050 | 0.000000 | 0.000200 |
| 95 | 18.000000 | 0.000128 | 0.000102 | -0.000100 | 0.000100 | 0.000150 | 0.000200 | 0.000300 |
| 96 | 18.000000 | 0.036689 | 0.202023 | -0.306200 | -0.044325 | 0.029350 | 0.139050 | 0.585400 |
| 97 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 98 | 18.000000 | -0.111244 | 0.406094 | -0.935300 | -0.216500 | -0.107100 | 0.097575 | 0.624100 |
| 99 | 18.000000 | 0.008739 | 0.045102 | -0.041900 | -0.018800 | -0.005100 | 0.020450 | 0.121800 |
| 100 | 18.000000 | 0.000061 | 0.000366 | -0.000400 | -0.000200 | 0.000050 | 0.000300 | 0.000800 |
| 101 | 18.000000 | -0.000050 | 0.000195 | -0.000400 | -0.000100 | -0.000050 | 0.000075 | 0.000300 |
| 102 | 18.000000 | 0.020028 | 0.061977 | -0.075200 | -0.010250 | 0.009100 | 0.049775 | 0.163800 |
| 103 | 18.000000 | -0.005194 | 0.001381 | -0.007500 | -0.005900 | -0.005000 | -0.004275 | -0.002600 |
| 104 | 18.000000 | -0.000089 | 0.000631 | -0.001600 | -0.000275 | 0.000150 | 0.000300 | 0.000600 |
| 105 | 18.000000 | 0.000867 | 0.003325 | -0.005200 | -0.000750 | 0.000250 | 0.002650 | 0.007800 |
| 106 | 18.000000 | 0.000933 | 0.001272 | -0.001900 | 0.000000 | 0.000850 | 0.001775 | 0.003300 |
| 107 | 18.000000 | -0.038622 | 0.112880 | -0.260100 | -0.072000 | -0.022600 | 0.027925 | 0.135900 |
| 108 | 18.000000 | -0.040056 | 0.136063 | -0.203800 | -0.117400 | -0.062250 | -0.009100 | 0.319600 |
| 109 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 110 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 111 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 112 | 18.000000 | 0.283794 | 0.232979 | 0.000000 | 0.000000 | 0.460600 | 0.464925 | 0.472700 |
| 113 | 18.000000 | 0.938967 | 0.010914 | 0.914400 | 0.935925 | 0.938700 | 0.944650 | 0.958700 |
| 114 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 115 | 18.000000 | 742.226317 | 42.219709 | 636.954700 | 726.798325 | 748.325850 | 767.609250 | 806.273400 |
| 116 | 18.000000 | 0.988294 | 0.006531 | 0.969200 | 0.990200 | 0.990550 | 0.990775 | 0.991100 |
| 117 | 18.000000 | 58.569439 | 0.720623 | 56.563500 | 58.443150 | 58.659750 | 58.811875 | 59.577600 |
| 118 | 18.000000 | 0.598628 | 0.006772 | 0.583200 | 0.595875 | 0.600300 | 0.602950 | 0.608100 |
| 119 | 18.000000 | 0.970106 | 0.007502 | 0.960700 | 0.963275 | 0.968750 | 0.976925 | 0.980400 |
| 120 | 18.000000 | 6.359483 | 0.094545 | 6.205300 | 6.307650 | 6.338450 | 6.408125 | 6.539800 |
| 121 | 18.000000 | 15.808889 | 0.081881 | 15.550000 | 15.772500 | 15.830000 | 15.872500 | 15.900000 |
| 122 | 18.000000 | 2.806500 | 0.362844 | 2.270000 | 2.549500 | 2.771500 | 3.144000 | 3.263000 |
| 123 | 18.000000 | 15.843889 | 0.083111 | 15.610000 | 15.820000 | 15.860000 | 15.890000 | 15.940000 |
| 124 | 18.000000 | 15.813889 | 0.082970 | 15.590000 | 15.800000 | 15.820000 | 15.855000 | 15.950000 |
| 125 | 18.000000 | 0.884994 | 0.133848 | 0.756800 | 0.818350 | 0.870300 | 0.898700 | 1.366000 |
| 126 | 18.000000 | 2.800000 | 0.214799 | 2.480000 | 2.645000 | 2.770500 | 2.854000 | 3.353000 |
| 127 | 18.000000 | 0.451594 | 0.073217 | 0.327300 | 0.413800 | 0.462200 | 0.515800 | 0.532800 |
| 128 | 18.000000 | 3.280167 | 0.101508 | 3.119000 | 3.207000 | 3.272000 | 3.362000 | 3.442000 |
| 129 | 18.000000 | -0.044683 | 0.422342 | -0.567700 | -0.402125 | -0.047300 | 0.000000 | 0.709600 |
| 130 | 18.000000 | 0.771944 | 0.029086 | 0.724300 | 0.748175 | 0.772050 | 0.786300 | 0.819400 |
| 131 | 18.000000 | 0.997822 | 0.002026 | 0.995100 | 0.996225 | 0.997450 | 0.999800 | 1.001000 |
| 132 | 18.000000 | 2.324528 | 0.032503 | 2.259200 | 2.302925 | 2.324300 | 2.343700 | 2.380200 |
| 133 | 18.000000 | 996.652683 | 5.770117 | 980.451000 | 993.127400 | 997.769450 | 998.460700 | 1004.805400 |
| 134 | 18.000000 | 39.483767 | 1.989793 | 36.957800 | 38.144800 | 39.325600 | 40.545800 | 45.131800 |
| 135 | 18.000000 | 102.833333 | 18.101836 | 70.000000 | 89.250000 | 96.500000 | 123.000000 | 127.000000 |
| 136 | 18.000000 | 143.411111 | 40.132500 | 64.100000 | 114.100000 | 143.700000 | 174.975000 | 209.200000 |
| 137 | 18.000000 | 128.044444 | 42.983091 | 71.900000 | 97.950000 | 122.800000 | 149.425000 | 211.900000 |
| 138 | 18.000000 | 52.805539 | 5.464771 | 45.100100 | 48.200000 | 52.949950 | 55.500000 | 64.099900 |
| 139 | 18.000000 | 264.827622 | 65.692141 | 162.432000 | 219.767900 | 250.149900 | 296.303000 | 380.590900 |
| 140 | 18.000000 | 0.252617 | 0.174362 | 0.057700 | 0.120200 | 0.210800 | 0.362375 | 0.626500 |
| 141 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 142 | 18.000000 | 6.301111 | 1.523718 | 3.640000 | 5.517500 | 5.820000 | 7.560000 | 8.400000 |
| 143 | 18.000000 | 0.003783 | 0.000660 | 0.002800 | 0.003400 | 0.003700 | 0.004175 | 0.004900 |
| 144 | 18.000000 | 0.098822 | 0.023463 | 0.063400 | 0.078875 | 0.095000 | 0.112925 | 0.135600 |
| 145 | 18.000000 | 0.068283 | 0.019846 | 0.039300 | 0.055850 | 0.063250 | 0.082450 | 0.109000 |
| 146 | 18.000000 | 0.049794 | 0.008704 | 0.035800 | 0.045850 | 0.049150 | 0.055750 | 0.062300 |
| 147 | 18.000000 | 0.025311 | 0.006771 | 0.014100 | 0.019650 | 0.023800 | 0.032350 | 0.034900 |
| 148 | 18.000000 | 11.157283 | 3.282740 | 5.611100 | 8.870300 | 12.549750 | 13.522500 | 14.235400 |
| 149 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 150 | 18.000000 | 7.806444 | 3.689287 | 4.271000 | 5.514000 | 7.189500 | 8.817500 | 19.388000 |
| 151 | 18.000000 | 12.489333 | 3.183335 | 6.621000 | 10.275000 | 12.051500 | 15.168750 | 18.186000 |
| 152 | 18.000000 | 0.683944 | 0.362626 | 0.351400 | 0.445875 | 0.523650 | 0.763525 | 1.389200 |
| 153 | 18.000000 | 0.016300 | 0.005146 | 0.010500 | 0.013775 | 0.015550 | 0.017850 | 0.034100 |
| 154 | 18.000000 | 10.587117 | 3.140285 | 5.276900 | 8.761800 | 11.934300 | 12.343325 | 13.904700 |
| 155 | 18.000000 | 1.118333 | 2.893366 | 0.350000 | 0.402500 | 0.465000 | 0.480000 | 12.710000 |
| 156 | 18.000000 | 0.051194 | 0.015435 | 0.020900 | 0.043475 | 0.050150 | 0.057725 | 0.086000 |
| 157 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 158 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 159 | 18.000000 | 2220.055556 | 2044.768604 | 233.000000 | 739.000000 | 1335.000000 | 2397.750000 | 5803.000000 |
| 160 | 18.000000 | 1065.277778 | 1089.298145 | 59.000000 | 346.000000 | 645.500000 | 952.750000 | 3530.000000 |
| 161 | 18.000000 | 1706.222222 | 1526.638852 | 295.000000 | 491.500000 | 1141.000000 | 3011.500000 | 4483.000000 |
| 162 | 18.000000 | 1293.111111 | 1138.325700 | 143.000000 | 407.750000 | 877.500000 | 1858.250000 | 3851.000000 |
| 163 | 18.000000 | 0.282167 | 0.356410 | 0.032000 | 0.076500 | 0.101000 | 0.180500 | 0.942000 |
| 164 | 18.000000 | 0.446667 | 0.731649 | 0.028000 | 0.044000 | 0.061500 | 0.135750 | 1.801000 |
| 165 | 18.000000 | 0.756667 | 1.266233 | 0.022000 | 0.072250 | 0.106500 | 0.243250 | 3.077000 |
| 166 | 18.000000 | 2.433333 | 0.625911 | 1.700000 | 2.025000 | 2.250000 | 2.800000 | 3.900000 |
| 167 | 18.000000 | 0.938889 | 0.185151 | 0.600000 | 0.900000 | 0.900000 | 1.000000 | 1.400000 |
| 168 | 18.000000 | 0.098000 | 0.021155 | 0.056000 | 0.080750 | 0.105000 | 0.116000 | 0.124000 |
| 169 | 18.000000 | 0.232278 | 0.184922 | 0.046000 | 0.096000 | 0.125000 | 0.368500 | 0.561000 |
| 170 | 18.000000 | 0.749489 | 0.196708 | 0.508700 | 0.588500 | 0.712350 | 0.908500 | 1.082400 |
| 171 | 18.000000 | 0.123283 | 0.093984 | 0.035600 | 0.037300 | 0.098000 | 0.151300 | 0.317600 |
| 172 | 18.000000 | 0.358944 | 0.065858 | 0.236400 | 0.314100 | 0.371400 | 0.422375 | 0.434300 |
| 173 | 18.000000 | 0.588717 | 0.078217 | 0.439100 | 0.556275 | 0.585900 | 0.647225 | 0.706400 |
| 174 | 18.000000 | 0.358972 | 0.065868 | 0.236400 | 0.314100 | 0.371500 | 0.422375 | 0.434300 |
| 175 | 18.000000 | 0.903622 | 0.100464 | 0.740800 | 0.835550 | 0.859650 | 0.963250 | 1.172000 |
| 176 | 18.000000 | 0.247794 | 0.066080 | 0.130800 | 0.204725 | 0.247000 | 0.276825 | 0.397900 |
| 177 | 18.000000 | 0.456833 | 0.294170 | 0.160000 | 0.226000 | 0.326000 | 0.709250 | 1.065000 |
| 178 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 179 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 180 | 18.000000 | 17.147222 | 2.561828 | 12.480000 | 15.120000 | 17.000000 | 19.020000 | 21.300000 |
| 181 | 18.000000 | 0.444278 | 0.160291 | 0.212000 | 0.339750 | 0.400000 | 0.502250 | 0.745000 |
| 182 | 18.000000 | 11.806667 | 2.501679 | 7.340000 | 10.307500 | 12.275000 | 13.937500 | 14.720000 |
| 183 | 18.000000 | 25.942222 | 7.725193 | 15.840000 | 20.517000 | 23.138500 | 34.643500 | 37.715000 |
| 184 | 18.000000 | 0.118667 | 0.040913 | 0.066400 | 0.089650 | 0.100400 | 0.151625 | 0.195900 |
| 185 | 18.000000 | 6.477778 | 2.105959 | 3.040000 | 5.120000 | 6.295000 | 7.842500 | 10.290000 |
| 186 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 187 | 18.000000 | 17.533889 | 5.017374 | 6.910000 | 14.870000 | 18.260000 | 21.162500 | 25.540000 |
| 188 | 18.000000 | 54.575667 | 20.520132 | 11.961000 | 39.847500 | 53.252000 | 71.772250 | 82.986000 |
| 189 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 190 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 191 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 192 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 193 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 194 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 195 | 18.000000 | 0.478778 | 1.034159 | 0.139000 | 0.224250 | 0.244000 | 0.265500 | 4.617000 |
| 196 | 18.000000 | 4.611667 | 1.397116 | 2.080000 | 3.612500 | 4.810000 | 5.485000 | 7.110000 |
| 197 | 18.000000 | 18.883333 | 3.520082 | 12.560000 | 15.987500 | 19.575000 | 20.572500 | 24.700000 |
| 198 | 18.000000 | 0.742222 | 0.349120 | 0.247000 | 0.480500 | 0.746500 | 1.020250 | 1.264000 |
| 199 | 18.000000 | 10.826667 | 2.520285 | 7.080000 | 9.432500 | 10.670000 | 11.797500 | 17.580000 |
| 200 | 18.000000 | 14.180000 | 4.130986 | 5.580000 | 11.745000 | 13.915000 | 17.112500 | 21.780000 |
| 201 | 18.000000 | 4.611667 | 1.397116 | 2.080000 | 3.612500 | 4.810000 | 5.485000 | 7.110000 |
| 202 | 18.000000 | 6.676500 | 2.668076 | 3.394000 | 4.669500 | 6.025500 | 8.051250 | 11.537000 |
| 203 | 18.000000 | 26.097383 | 7.934344 | 15.078000 | 21.219000 | 23.733500 | 33.345500 | 41.002000 |
| 204 | 18.000000 | 0.319150 | 0.183618 | 0.062600 | 0.186975 | 0.314550 | 0.404550 | 0.715100 |
| 205 | 18.000000 | 10.822222 | 4.710149 | 6.230000 | 7.297500 | 9.325000 | 12.672500 | 24.970000 |
| 206 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 207 | 18.000000 | 18.632222 | 7.241750 | 8.020000 | 12.985000 | 17.650000 | 21.845000 | 34.990000 |
| 208 | 18.000000 | 92.445389 | 25.076448 | 36.619000 | 73.648000 | 94.810500 | 112.826500 | 134.250000 |
| 209 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 210 | 18.000000 | 0.084822 | 0.040456 | 0.033900 | 0.057550 | 0.067300 | 0.116675 | 0.158700 |
| 211 | 18.000000 | 0.056133 | 0.019745 | 0.018900 | 0.048950 | 0.052800 | 0.060725 | 0.112700 |
| 212 | 18.000000 | 0.079633 | 0.034643 | 0.032400 | 0.060525 | 0.077200 | 0.094375 | 0.165100 |
| 213 | 18.000000 | 0.141061 | 0.286588 | 0.035400 | 0.056025 | 0.070000 | 0.088325 | 1.283700 |
| 214 | 18.000000 | 0.063356 | 0.021284 | 0.028300 | 0.047450 | 0.068000 | 0.081650 | 0.091500 |
| 215 | 18.000000 | 0.077039 | 0.031327 | 0.033800 | 0.052375 | 0.078200 | 0.098250 | 0.159900 |
| 216 | 18.000000 | 0.069000 | 0.024951 | 0.021500 | 0.048250 | 0.080100 | 0.088475 | 0.099800 |
| 217 | 18.000000 | 0.102972 | 0.114465 | 0.037800 | 0.058225 | 0.073250 | 0.099425 | 0.552200 |
| 218 | 18.000000 | 3.670861 | 1.349350 | 1.906200 | 2.881850 | 3.323500 | 4.089800 | 7.561600 |
| 219 | 18.000000 | 0.003333 | 0.002482 | 0.001000 | 0.001775 | 0.003000 | 0.003800 | 0.011700 |
| 220 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 221 | 18.000000 | 0.078439 | 0.016206 | 0.040100 | 0.073200 | 0.082800 | 0.089825 | 0.096300 |
| 222 | 18.000000 | 0.008994 | 0.013013 | 0.000400 | 0.001500 | 0.003700 | 0.008175 | 0.050900 |
| 223 | 18.000000 | 124.373617 | 38.399405 | 65.358200 | 101.497750 | 128.800800 | 148.941875 | 182.495600 |
| 224 | 18.000000 | 0.195661 | 0.379483 | 0.023800 | 0.040100 | 0.064300 | 0.097250 | 1.436100 |
| 225 | 18.000000 | 1157.938828 | 391.712482 | 606.299800 | 841.350350 | 1118.399900 | 1357.650150 | 1988.000000 |
| 226 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 227 | 18.000000 | 0.028622 | 0.014966 | 0.013400 | 0.018000 | 0.022650 | 0.036800 | 0.074400 |
| 228 | 18.000000 | 0.024567 | 0.011506 | 0.012300 | 0.017025 | 0.022200 | 0.026300 | 0.054600 |
| 229 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 230 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 231 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 232 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 233 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 234 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 235 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 236 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 237 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 238 | 18.000000 | 0.005506 | 0.001562 | 0.002600 | 0.004600 | 0.006050 | 0.006675 | 0.008200 |
| 239 | 18.000000 | 0.004428 | 0.001122 | 0.003100 | 0.003675 | 0.004000 | 0.004775 | 0.007200 |
| 240 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 241 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 242 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 243 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 244 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 245 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 246 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 247 | 18.000000 | 0.040556 | 0.054699 | 0.000000 | 0.000000 | 0.026150 | 0.054950 | 0.178500 |
| 248 | 18.000000 | 0.029511 | 0.022953 | 0.010700 | 0.019050 | 0.023450 | 0.030525 | 0.113100 |
| 249 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 250 | 18.000000 | 124.315067 | 45.720668 | 53.607800 | 96.672600 | 126.029650 | 148.987400 | 219.945300 |
| 251 | 18.000000 | 0.002022 | 0.004557 | 0.000600 | 0.000700 | 0.000950 | 0.001075 | 0.020200 |
| 252 | 18.000000 | 3.229944 | 0.620336 | 2.577500 | 2.796975 | 3.006600 | 3.473000 | 4.884700 |
| 253 | 18.000000 | 0.033072 | 0.012841 | 0.017700 | 0.025750 | 0.031050 | 0.039150 | 0.073300 |
| 254 | 18.000000 | 0.014267 | 0.008901 | 0.003700 | 0.005700 | 0.013900 | 0.021025 | 0.030100 |
| 255 | 18.000000 | 0.421872 | 0.069755 | 0.288100 | 0.386000 | 0.424050 | 0.446800 | 0.574900 |
| 256 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 257 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 258 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 259 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 260 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 261 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 262 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 263 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 264 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 265 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 266 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 267 | 18.000000 | 0.038100 | 0.007869 | 0.026300 | 0.033150 | 0.035100 | 0.045675 | 0.051300 |
| 268 | 18.000000 | 30.226611 | 5.426063 | 19.862000 | 27.861000 | 29.682000 | 32.201000 | 40.855000 |
| 269 | 18.000000 | 3.327656 | 0.716224 | 2.289400 | 2.826425 | 3.406100 | 3.843150 | 4.515200 |
| 270 | 18.000000 | 28.310622 | 4.301186 | 19.095200 | 24.498175 | 29.228200 | 30.981500 | 34.125000 |
| 271 | 18.000000 | 50.411983 | 15.739722 | 19.982200 | 38.731700 | 53.031550 | 58.200525 | 78.378500 |
| 272 | 18.000000 | 44.022878 | 15.357001 | 22.316300 | 33.412350 | 44.312050 | 52.545400 | 72.131600 |
| 273 | 18.000000 | 18.274633 | 1.991947 | 15.771600 | 17.400800 | 17.486400 | 19.510900 | 22.627100 |
| 274 | 18.000000 | 87.578117 | 19.863936 | 50.363100 | 83.554200 | 90.797850 | 92.948200 | 120.740800 |
| 275 | 18.000000 | 0.080378 | 0.051731 | 0.021600 | 0.039950 | 0.068850 | 0.109200 | 0.189600 |
| 276 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 277 | 18.000000 | 2.195022 | 0.587310 | 1.092900 | 1.845900 | 2.288900 | 2.585775 | 3.052800 |
| 278 | 18.000000 | 0.000994 | 0.000207 | 0.000700 | 0.000825 | 0.000950 | 0.001200 | 0.001300 |
| 279 | 18.000000 | 0.033733 | 0.008633 | 0.022600 | 0.025250 | 0.032300 | 0.041100 | 0.051900 |
| 280 | 18.000000 | 0.018011 | 0.004661 | 0.011300 | 0.015600 | 0.016900 | 0.020950 | 0.028200 |
| 281 | 18.000000 | 0.014250 | 0.002217 | 0.009700 | 0.012875 | 0.014600 | 0.016150 | 0.017200 |
| 282 | 18.000000 | 0.008433 | 0.002248 | 0.004800 | 0.006525 | 0.008000 | 0.010825 | 0.011600 |
| 283 | 18.000000 | 3.566533 | 1.008968 | 1.795000 | 3.113125 | 3.978900 | 4.271400 | 4.423900 |
| 284 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 285 | 18.000000 | 2.400728 | 1.042494 | 1.408200 | 1.626875 | 2.189300 | 2.774700 | 5.674100 |
| 286 | 18.000000 | 3.617700 | 0.618350 | 2.223100 | 3.327325 | 3.716850 | 3.939225 | 4.584500 |
| 287 | 18.000000 | 0.206489 | 0.109555 | 0.103500 | 0.130350 | 0.154650 | 0.270600 | 0.412700 |
| 288 | 18.000000 | 0.005372 | 0.001643 | 0.003400 | 0.004500 | 0.005250 | 0.005975 | 0.010900 |
| 289 | 18.000000 | 3.424172 | 0.999068 | 1.684100 | 3.048275 | 3.884300 | 4.002325 | 4.347400 |
| 290 | 18.000000 | 0.357656 | 1.012988 | 0.091600 | 0.108550 | 0.127500 | 0.128600 | 4.416300 |
| 291 | 18.000000 | 0.016739 | 0.005071 | 0.007500 | 0.013450 | 0.017500 | 0.018375 | 0.025100 |
| 292 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 293 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 294 | 18.000000 | 1092.598578 | 1088.141965 | 106.497300 | 327.861900 | 588.844100 | 1079.456425 | 3153.676400 |
| 295 | 18.000000 | 508.338239 | 565.302546 | 26.587900 | 147.386625 | 271.698600 | 396.920350 | 1768.640600 |
| 296 | 18.000000 | 838.907483 | 812.273651 | 128.014000 | 212.185100 | 506.062450 | 1379.414300 | 2390.501600 |
| 297 | 18.000000 | 598.755300 | 528.931238 | 68.704700 | 182.385550 | 421.081750 | 895.582225 | 1792.156500 |
| 298 | 18.000000 | 0.142900 | 0.193178 | 0.014800 | 0.032400 | 0.043750 | 0.078875 | 0.525500 |
| 299 | 18.000000 | 0.235106 | 0.396120 | 0.011600 | 0.019675 | 0.026350 | 0.065800 | 1.025900 |
| 300 | 18.000000 | 0.398611 | 0.682433 | 0.010200 | 0.034025 | 0.047050 | 0.111975 | 1.769000 |
| 301 | 18.000000 | 0.824650 | 0.198515 | 0.583100 | 0.683875 | 0.782700 | 0.934300 | 1.350000 |
| 302 | 18.000000 | 0.309339 | 0.053668 | 0.202800 | 0.282050 | 0.310400 | 0.345900 | 0.403100 |
| 303 | 18.000000 | 0.032989 | 0.007264 | 0.020000 | 0.028725 | 0.033800 | 0.039150 | 0.042700 |
| 304 | 18.000000 | 0.076089 | 0.059374 | 0.017400 | 0.031125 | 0.041850 | 0.127425 | 0.182200 |
| 305 | 18.000000 | 0.281017 | 0.066371 | 0.211000 | 0.216200 | 0.279200 | 0.339200 | 0.384600 |
| 306 | 18.000000 | 0.050039 | 0.038411 | 0.012800 | 0.015725 | 0.043300 | 0.058525 | 0.137900 |
| 307 | 18.000000 | 0.143244 | 0.024014 | 0.099400 | 0.130150 | 0.148600 | 0.164575 | 0.170700 |
| 308 | 18.000000 | 0.230494 | 0.026948 | 0.170100 | 0.226600 | 0.238650 | 0.244100 | 0.263000 |
| 309 | 18.000000 | 0.143261 | 0.024024 | 0.099400 | 0.130175 | 0.148600 | 0.164650 | 0.170700 |
| 310 | 18.000000 | 0.344161 | 0.037390 | 0.283900 | 0.314500 | 0.346500 | 0.367525 | 0.443800 |
| 311 | 18.000000 | 0.097911 | 0.027302 | 0.058200 | 0.073750 | 0.095000 | 0.117500 | 0.143100 |
| 312 | 18.000000 | 0.184289 | 0.115337 | 0.061000 | 0.100900 | 0.126100 | 0.294600 | 0.417100 |
| 313 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 314 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 315 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 316 | 18.000000 | 5.368406 | 0.627123 | 4.382400 | 4.919550 | 5.244300 | 5.706575 | 6.551100 |
| 317 | 18.000000 | 0.144983 | 0.058184 | 0.065300 | 0.110700 | 0.131000 | 0.166500 | 0.270100 |
| 318 | 18.000000 | 3.366550 | 0.654584 | 2.250900 | 2.933225 | 3.642550 | 3.848075 | 4.268900 |
| 319 | 18.000000 | 7.669811 | 2.121096 | 5.168500 | 6.262775 | 6.832800 | 9.943650 | 11.058300 |
| 320 | 18.000000 | 0.034394 | 0.009985 | 0.020600 | 0.025475 | 0.032900 | 0.043850 | 0.054600 |
| 321 | 18.000000 | 1.929011 | 0.647126 | 0.880300 | 1.640125 | 1.773150 | 2.388125 | 3.179200 |
| 322 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 323 | 18.000000 | 5.139433 | 1.448022 | 2.164600 | 4.620025 | 5.168550 | 5.949500 | 7.329600 |
| 324 | 18.000000 | 16.107106 | 6.222344 | 3.309100 | 11.289650 | 15.707300 | 22.690100 | 25.289200 |
| 325 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 326 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 327 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 328 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 329 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 330 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 331 | 18.000000 | 0.103144 | 0.139272 | 0.024300 | 0.075850 | 0.078900 | 0.081450 | 0.654200 |
| 332 | 18.000000 | 1.377106 | 0.417829 | 0.657900 | 1.091300 | 1.491150 | 1.615925 | 1.991100 |
| 333 | 18.000000 | 5.722456 | 0.757860 | 4.460000 | 5.138800 | 5.826100 | 6.278875 | 6.902300 |
| 334 | 18.000000 | 0.231494 | 0.113225 | 0.072500 | 0.128275 | 0.247600 | 0.333950 | 0.400200 |
| 335 | 18.000000 | 3.106761 | 0.684282 | 2.076300 | 2.647225 | 3.209950 | 3.359875 | 5.001400 |
| 336 | 18.000000 | 9.067739 | 1.181853 | 7.742100 | 8.172150 | 8.725950 | 9.683775 | 11.551100 |
| 337 | 18.000000 | 1.377106 | 0.417829 | 0.657900 | 1.091300 | 1.491150 | 1.615925 | 1.991100 |
| 338 | 18.000000 | 1.941894 | 0.668444 | 1.126500 | 1.433675 | 1.810750 | 2.475625 | 3.067200 |
| 339 | 18.000000 | 7.725367 | 2.134540 | 5.010800 | 6.236250 | 6.873550 | 9.667400 | 11.444500 |
| 340 | 18.000000 | 0.095756 | 0.056152 | 0.020900 | 0.055175 | 0.088300 | 0.127675 | 0.229000 |
| 341 | 18.000000 | 3.246850 | 1.138390 | 1.927800 | 2.425775 | 3.058400 | 3.755775 | 6.275800 |
| 342 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 343 | 18.000000 | 5.587550 | 2.066794 | 2.489000 | 3.837300 | 5.572700 | 6.949025 | 9.585400 |
| 344 | 18.000000 | 28.821594 | 7.829269 | 11.001800 | 23.006100 | 30.866450 | 34.737750 | 41.708000 |
| 345 | 18.000000 | 3.463744 | 4.683529 | 0.000000 | 0.000000 | 0.000000 | 6.021300 | 13.566400 |
| 346 | 18.000000 | 2.958572 | 4.313228 | 0.000000 | 0.000000 | 0.000000 | 4.685100 | 15.448800 |
| 347 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 348 | 18.000000 | 0.024861 | 0.012573 | 0.010300 | 0.015850 | 0.021550 | 0.035675 | 0.047300 |
| 349 | 18.000000 | 0.024478 | 0.008287 | 0.008100 | 0.021125 | 0.023300 | 0.028600 | 0.047700 |
| 350 | 18.000000 | 0.035972 | 0.016060 | 0.014000 | 0.027025 | 0.032850 | 0.042825 | 0.076800 |
| 351 | 18.000000 | 0.065794 | 0.138656 | 0.016700 | 0.024775 | 0.032800 | 0.038000 | 0.618800 |
| 352 | 18.000000 | 0.018967 | 0.005797 | 0.008900 | 0.014400 | 0.019900 | 0.024425 | 0.027300 |
| 353 | 18.000000 | 0.038394 | 0.015694 | 0.014600 | 0.026925 | 0.042250 | 0.050300 | 0.073900 |
| 354 | 18.000000 | 0.033872 | 0.013911 | 0.009300 | 0.021075 | 0.039400 | 0.044875 | 0.051300 |
| 355 | 18.000000 | 0.048783 | 0.052823 | 0.015900 | 0.026450 | 0.037400 | 0.048925 | 0.254800 |
| 356 | 18.000000 | 1.269372 | 0.422437 | 0.722300 | 1.003350 | 1.194750 | 1.495850 | 2.460000 |
| 357 | 18.000000 | 0.001061 | 0.000755 | 0.000400 | 0.000525 | 0.000950 | 0.001250 | 0.003600 |
| 358 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 359 | 18.000000 | 0.025406 | 0.005912 | 0.011300 | 0.022750 | 0.027100 | 0.029575 | 0.034900 |
| 360 | 18.000000 | 0.002900 | 0.004138 | 0.000100 | 0.000525 | 0.001250 | 0.002775 | 0.015900 |
| 361 | 18.000000 | 40.343000 | 11.175609 | 21.031200 | 36.657125 | 42.574100 | 45.447850 | 58.057500 |
| 362 | 18.000000 | 0.059367 | 0.112466 | 0.006900 | 0.012025 | 0.021200 | 0.031100 | 0.416300 |
| 363 | 18.000000 | 384.976667 | 131.219620 | 205.529000 | 290.208500 | 375.719300 | 478.285500 | 677.187300 |
| 364 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 365 | 18.000000 | 0.007594 | 0.003398 | 0.003800 | 0.005325 | 0.006300 | 0.009100 | 0.017000 |
| 366 | 18.000000 | 0.006789 | 0.003166 | 0.003200 | 0.004800 | 0.006000 | 0.007575 | 0.014800 |
| 367 | 18.000000 | 0.004856 | 0.002922 | 0.000000 | 0.002925 | 0.003600 | 0.006625 | 0.012400 |
| 368 | 18.000000 | 0.004422 | 0.002898 | 0.000000 | 0.002700 | 0.003550 | 0.005850 | 0.011400 |
| 369 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 370 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 371 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 372 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 373 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 374 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 375 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 376 | 18.000000 | 0.001878 | 0.000546 | 0.000800 | 0.001600 | 0.001950 | 0.002200 | 0.003000 |
| 377 | 18.000000 | 0.001578 | 0.000380 | 0.001100 | 0.001325 | 0.001400 | 0.001775 | 0.002400 |
| 378 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 379 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 380 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 381 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 382 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 383 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 384 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 385 | 18.000000 | 0.007056 | 0.009005 | 0.000000 | 0.000000 | 0.005700 | 0.009150 | 0.033600 |
| 386 | 18.000000 | 0.009861 | 0.006920 | 0.003200 | 0.005800 | 0.008000 | 0.011425 | 0.033800 |
| 387 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 388 | 18.000000 | 41.583456 | 15.815848 | 13.976900 | 29.655750 | 41.455450 | 55.866925 | 65.099900 |
| 389 | 18.000000 | 0.000617 | 0.001373 | 0.000200 | 0.000200 | 0.000300 | 0.000300 | 0.006100 |
| 390 | 18.000000 | 1.034917 | 0.147825 | 0.820700 | 0.932750 | 0.999400 | 1.123025 | 1.403700 |
| 391 | 18.000000 | 0.010767 | 0.003157 | 0.006500 | 0.008400 | 0.010150 | 0.012950 | 0.019000 |
| 392 | 18.000000 | 0.004767 | 0.002947 | 0.001100 | 0.001925 | 0.005100 | 0.007425 | 0.009200 |
| 393 | 18.000000 | 0.142928 | 0.020972 | 0.107200 | 0.132375 | 0.140250 | 0.147825 | 0.192100 |
| 394 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 395 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 396 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 397 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 398 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 399 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 400 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 401 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 402 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 403 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 404 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 405 | 18.000000 | 0.012528 | 0.002871 | 0.008700 | 0.010425 | 0.012000 | 0.014425 | 0.019000 |
| 406 | 18.000000 | 11.210561 | 2.175442 | 7.149300 | 9.796575 | 10.871700 | 12.566800 | 14.239600 |
| 407 | 18.000000 | 1.044367 | 0.250571 | 0.791000 | 0.804100 | 1.032300 | 1.187975 | 1.624800 |
| 408 | 18.000000 | 4.649806 | 0.800537 | 3.127200 | 4.078200 | 4.329600 | 5.570650 | 5.636300 |
| 409 | 18.000000 | 4.778494 | 1.331242 | 2.195200 | 3.875600 | 4.774050 | 5.733625 | 7.058100 |
| 410 | 18.000000 | 5.063917 | 1.673559 | 2.867500 | 3.825875 | 4.933400 | 5.986850 | 8.726000 |
| 411 | 18.000000 | 2.375661 | 0.242800 | 2.062700 | 2.176525 | 2.418050 | 2.467900 | 2.881400 |
| 412 | 18.000000 | 22.919622 | 7.243083 | 14.303600 | 16.155850 | 22.737800 | 24.885200 | 36.380300 |
| 413 | 18.000000 | 20.184878 | 12.139440 | 7.321000 | 8.845225 | 18.055800 | 27.746400 | 44.909400 |
| 414 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 415 | 18.000000 | 6.115011 | 1.457461 | 3.625600 | 5.356875 | 5.644900 | 7.116000 | 8.723600 |
| 416 | 18.000000 | 3.096550 | 0.510180 | 2.258100 | 2.770975 | 3.026300 | 3.461050 | 3.930000 |
| 417 | 18.000000 | 6.548439 | 1.537005 | 4.217800 | 5.404575 | 6.184000 | 7.612075 | 9.060400 |
| 418 | 18.000000 | 338.731172 | 191.120192 | 0.000000 | 288.741050 | 336.963200 | 439.449250 | 692.547700 |
| 419 | 18.000000 | 280.717739 | 347.704241 | 0.000000 | 0.000000 | 118.422100 | 447.044375 | 979.257400 |
| 420 | 18.000000 | 2.655306 | 0.733269 | 1.457700 | 2.040025 | 2.484100 | 3.424575 | 3.695500 |
| 421 | 18.000000 | 5.517811 | 1.594989 | 2.874900 | 4.250500 | 6.234100 | 6.680225 | 7.049200 |
| 422 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 423 | 18.000000 | 73.344572 | 25.199419 | 44.960200 | 54.543100 | 61.938550 | 88.050150 | 141.650800 |
| 424 | 18.000000 | 2.989889 | 0.754233 | 1.615300 | 2.479725 | 2.867600 | 3.648100 | 4.399500 |
| 425 | 18.000000 | 7.051833 | 3.760790 | 3.375100 | 4.337575 | 5.644650 | 7.838100 | 14.314700 |
| 426 | 18.000000 | 1.686172 | 0.546225 | 1.083300 | 1.424925 | 1.602700 | 1.847875 | 3.586300 |
| 427 | 18.000000 | 5.500833 | 1.604001 | 2.843200 | 4.403125 | 6.224550 | 6.422425 | 7.257000 |
| 428 | 18.000000 | 9.897961 | 27.169840 | 2.804900 | 3.234500 | 3.718900 | 3.831900 | 118.753300 |
| 429 | 18.000000 | 3.642583 | 1.093797 | 1.510000 | 3.084050 | 3.565200 | 4.064600 | 6.112700 |
| 430 | 18.000000 | 69.640306 | 105.446570 | 4.318400 | 13.500375 | 24.109700 | 39.458775 | 400.000000 |
| 431 | 18.000000 | 69.494794 | 108.571046 | 2.265500 | 12.087200 | 23.279500 | 32.569225 | 400.000000 |
| 432 | 18.000000 | 72.633689 | 104.241338 | 7.623200 | 12.847500 | 29.988050 | 67.979525 | 400.000000 |
| 433 | 18.000000 | 174.573611 | 159.847986 | 0.000000 | 54.624175 | 130.901350 | 211.389100 | 597.161300 |
| 434 | 18.000000 | 59.314817 | 108.616890 | 3.428900 | 8.093875 | 9.246900 | 13.718600 | 400.000000 |
| 435 | 18.000000 | 54.778094 | 109.961985 | 1.569900 | 2.357525 | 3.227800 | 6.795050 | 400.000000 |
| 436 | 18.000000 | 53.775189 | 110.593828 | 0.709800 | 1.478600 | 2.281450 | 4.164975 | 400.000000 |
| 437 | 18.000000 | 3.793394 | 1.012344 | 2.682300 | 3.117225 | 3.535600 | 4.589450 | 6.206900 |
| 438 | 18.000000 | 40.312272 | 9.868340 | 24.107100 | 33.742075 | 40.691700 | 44.408525 | 60.000000 |
| 439 | 18.000000 | 50.727661 | 13.213138 | 32.605500 | 39.251400 | 49.302000 | 59.672575 | 76.015900 |
| 440 | 18.000000 | 6.717578 | 5.439708 | 1.307100 | 2.734475 | 3.582250 | 10.564500 | 16.417400 |
| 441 | 18.000000 | 0.882628 | 0.235511 | 0.595500 | 0.684100 | 0.846000 | 1.072875 | 1.277100 |
| 442 | 18.000000 | 1.329239 | 0.961687 | 0.388700 | 0.426400 | 1.122700 | 1.680050 | 3.291800 |
| 443 | 18.000000 | 0.712456 | 0.129957 | 0.472200 | 0.626300 | 0.740000 | 0.838075 | 0.860200 |
| 444 | 18.000000 | 0.917617 | 0.120991 | 0.684900 | 0.866425 | 0.912550 | 1.012525 | 1.096900 |
| 445 | 18.000000 | 0.723472 | 0.133584 | 0.473400 | 0.630100 | 0.745800 | 0.849325 | 0.877200 |
| 446 | 18.000000 | 1.372600 | 0.155853 | 1.117400 | 1.262750 | 1.314100 | 1.461875 | 1.763900 |
| 447 | 18.000000 | 0.285783 | 0.076539 | 0.151800 | 0.232400 | 0.284100 | 0.320225 | 0.457600 |
| 448 | 18.000000 | 0.383506 | 0.240903 | 0.136200 | 0.192500 | 0.274950 | 0.600150 | 0.873900 |
| 449 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 450 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 451 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 452 | 18.000000 | 4.790539 | 0.737857 | 3.476700 | 4.213050 | 4.673750 | 5.287950 | 6.082700 |
| 453 | 18.000000 | 4.477033 | 1.653633 | 2.133400 | 3.372200 | 4.066200 | 5.148025 | 7.541800 |
| 454 | 18.000000 | 8.534967 | 2.040953 | 5.018100 | 7.022375 | 9.209200 | 10.105825 | 11.130300 |
| 455 | 18.000000 | 3.490928 | 0.989409 | 2.189400 | 2.747875 | 3.179350 | 4.640625 | 4.994300 |
| 456 | 18.000000 | 10.367628 | 3.010483 | 5.433000 | 8.058500 | 10.517250 | 12.631725 | 15.453900 |
| 457 | 18.000000 | 4.655000 | 1.541447 | 2.200700 | 3.713200 | 4.407650 | 5.707300 | 7.503300 |
| 458 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 459 | 18.000000 | 2.745944 | 0.764296 | 1.095100 | 2.349175 | 2.881650 | 3.305900 | 3.824800 |
| 460 | 18.000000 | 28.463583 | 8.344398 | 8.948800 | 22.539475 | 30.118350 | 33.680375 | 42.826100 |
| 461 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 462 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 463 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 464 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 465 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 466 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 467 | 18.000000 | 10.531911 | 23.104953 | 3.030100 | 4.807100 | 5.272900 | 5.810825 | 102.994700 |
| 468 | 18.000000 | 89.982794 | 132.300374 | 8.292200 | 19.491000 | 23.821850 | 77.647425 | 463.288300 |
| 469 | 18.000000 | 5.266511 | 0.964129 | 3.459200 | 4.474150 | 5.459050 | 5.725400 | 6.858500 |
| 470 | 18.000000 | 7.394172 | 3.551439 | 2.382200 | 4.546825 | 7.619100 | 10.370725 | 12.378600 |
| 471 | 18.000000 | 8.924561 | 1.881712 | 6.107800 | 7.576200 | 9.120500 | 9.751025 | 13.491100 |
| 472 | 18.000000 | 141.514944 | 60.576768 | 63.798700 | 95.643050 | 132.362100 | 172.999800 | 285.900000 |
| 473 | 18.000000 | 28.257444 | 14.114893 | 9.211100 | 17.190825 | 22.124500 | 38.792725 | 56.473700 |
| 474 | 18.000000 | 28.226883 | 13.480042 | 13.101000 | 15.449575 | 26.316550 | 38.355850 | 52.693500 |
| 475 | 18.000000 | 3.633939 | 1.044798 | 2.162700 | 2.963450 | 3.341700 | 4.501925 | 5.635500 |
| 476 | 18.000000 | 33.103533 | 18.658975 | 6.622500 | 20.958875 | 30.408900 | 44.352625 | 71.765700 |
| 477 | 18.000000 | 7.346733 | 3.233881 | 4.147700 | 4.999475 | 6.336250 | 8.729775 | 16.970100 |
| 478 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 479 | 18.000000 | 2.961489 | 1.126178 | 1.292800 | 2.124075 | 2.830850 | 3.490450 | 5.506000 |
| 480 | 18.000000 | 116.790228 | 37.862586 | 34.984000 | 96.776825 | 122.331500 | 142.073150 | 167.725600 |
| 481 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 482 | 18.000000 | 448.740922 | 310.429448 | 0.000000 | 235.300825 | 420.450450 | 672.506050 | 994.109400 |
| 483 | 18.000000 | 178.373722 | 136.322333 | 46.824600 | 91.555575 | 105.086650 | 242.239300 | 509.090900 |
| 484 | 18.000000 | 250.890894 | 331.770396 | 0.000000 | 0.000000 | 62.157350 | 478.543925 | 981.432400 |
| 485 | 18.000000 | 278.931311 | 281.220502 | 0.000000 | 124.290750 | 183.818050 | 334.920625 | 892.193300 |
| 486 | 18.000000 | 238.489078 | 284.621088 | 0.000000 | 0.000000 | 129.333050 | 428.452725 | 843.113800 |
| 487 | 18.000000 | 167.171994 | 228.794179 | 0.000000 | 48.873100 | 80.137950 | 126.759300 | 820.790000 |
| 488 | 18.000000 | 288.814533 | 248.460311 | 0.000000 | 121.230400 | 202.415000 | 389.611725 | 748.178100 |
| 489 | 18.000000 | 261.805611 | 188.162579 | 0.000000 | 167.553400 | 266.197700 | 332.648650 | 644.504000 |
| 490 | 18.000000 | 51.114122 | 21.801330 | 22.659400 | 37.044425 | 46.698750 | 57.945375 | 121.635900 |
| 491 | 18.000000 | 2.441711 | 1.747176 | 0.757800 | 1.300525 | 2.295500 | 2.623775 | 8.219900 |
| 492 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 493 | 18.000000 | 3.258761 | 0.646372 | 1.746600 | 3.104500 | 3.410600 | 3.638900 | 3.923800 |
| 494 | 18.000000 | 0.918250 | 1.326001 | 0.037200 | 0.150100 | 0.379550 | 0.832575 | 5.180000 |
| 495 | 18.000000 | 7.043822 | 2.264259 | 3.754800 | 5.813850 | 6.977050 | 8.424725 | 10.825100 |
| 496 | 18.000000 | 42.150722 | 27.365194 | 12.678800 | 21.954950 | 35.156900 | 53.667450 | 107.690500 |
| 497 | 18.000000 | 13.347372 | 4.713959 | 7.065000 | 9.642325 | 13.217350 | 15.285250 | 23.646900 |
| 498 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 499 | 18.000000 | 257.926672 | 336.660619 | 0.000000 | 0.000000 | 0.000000 | 441.876625 | 935.764400 |
| 500 | 18.000000 | 242.330578 | 357.238022 | 0.000000 | 0.000000 | 0.000000 | 668.687550 | 927.457600 |
| 501 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 502 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 503 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 504 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 505 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 506 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 507 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 508 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 509 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 510 | 18.000000 | 116.257739 | 58.846305 | 55.026500 | 71.331550 | 92.279250 | 140.723050 | 263.453800 |
| 511 | 18.000000 | 176.861750 | 279.594218 | 0.000000 | 0.000000 | 0.000000 | 357.539275 | 748.387100 |
| 512 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 513 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 514 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 515 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 516 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 517 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 518 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 519 | 18.000000 | 8.744244 | 11.827494 | 0.000000 | 0.000000 | 5.632550 | 11.860050 | 39.105800 |
| 520 | 18.000000 | 3.156167 | 2.493032 | 1.144400 | 2.015475 | 2.496400 | 3.262375 | 12.256000 |
| 521 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 522 | 18.000000 | 16.817783 | 6.342374 | 7.385900 | 13.133175 | 16.286500 | 20.903775 | 29.380400 |
| 523 | 18.000000 | 0.207011 | 0.471587 | 0.061600 | 0.070775 | 0.092950 | 0.107225 | 2.088200 |
| 524 | 18.000000 | 5.522322 | 1.111098 | 4.414600 | 4.749800 | 5.085650 | 5.906750 | 8.543900 |
| 525 | 18.000000 | 5.520367 | 2.135894 | 2.995400 | 4.257125 | 5.197600 | 6.462350 | 12.183100 |
| 526 | 18.000000 | 1.477450 | 0.928573 | 0.378300 | 0.585700 | 1.436250 | 2.180250 | 3.131100 |
| 527 | 18.000000 | 6.630367 | 1.055994 | 4.506200 | 6.185550 | 6.589550 | 7.069975 | 8.837000 |
| 528 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 529 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 530 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 531 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 532 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 533 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 534 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 535 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 536 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 537 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 538 | 18.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 539 | 18.000000 | 1.639072 | 0.335983 | 1.129900 | 1.418975 | 1.510600 | 1.990500 | 2.156500 |
| 540 | 18.000000 | 3.031811 | 0.538426 | 1.999900 | 2.806200 | 2.973300 | 3.204700 | 4.082500 |
| 541 | 18.000000 | 8.435506 | 1.808640 | 5.808600 | 7.166500 | 8.463300 | 9.554825 | 11.507400 |
| 542 | 18.000000 | 0.109600 | 0.000000 | 0.109600 | 0.109600 | 0.109600 | 0.109600 | 0.109600 |
| 543 | 18.000000 | 0.007800 | 0.000000 | 0.007800 | 0.007800 | 0.007800 | 0.007800 | 0.007800 |
| 544 | 18.000000 | 0.002600 | 0.000000 | 0.002600 | 0.002600 | 0.002600 | 0.002600 | 0.002600 |
| 545 | 18.000000 | 7.116000 | 0.000000 | 7.116000 | 7.116000 | 7.116000 | 7.116000 | 7.116000 |
| 546 | 18.000000 | 0.977067 | 0.417602 | 0.000000 | 0.751475 | 0.984250 | 1.255800 | 1.837300 |
| 547 | 18.000000 | 380.397556 | 95.382570 | 0.000000 | 399.026000 | 402.922000 | 408.817500 | 412.222000 |
| 548 | 18.000000 | 71.582889 | 18.100453 | 0.000000 | 73.854500 | 74.647000 | 75.971500 | 81.582000 |
| 549 | 18.000000 | 0.603517 | 0.469982 | 0.000000 | 0.198475 | 0.582400 | 0.863300 | 1.880400 |
| 550 | 18.000000 | 21.535556 | 27.796293 | 0.000000 | 14.350000 | 16.030000 | 17.465000 | 131.680000 |
| 551 | 18.000000 | 3.164444 | 9.037159 | 0.000000 | 0.850000 | 1.015000 | 1.352500 | 39.330000 |
| 552 | 18.000000 | 0.248817 | 0.184420 | 0.000000 | 0.087500 | 0.234000 | 0.346825 | 0.681200 |
| 553 | 18.000000 | 9.583189 | 11.980174 | 0.000000 | 6.486200 | 7.153750 | 7.872775 | 56.930300 |
| 554 | 18.000000 | 1.376044 | 4.022449 | 0.000000 | 0.363650 | 0.424300 | 0.541900 | 17.478100 |
| 555 | 18.000000 | 55.077178 | 36.518684 | 0.000000 | 30.231325 | 52.444450 | 71.857400 | 161.408100 |
| 556 | 18.000000 | 5.474594 | 7.516773 | 0.000000 | 3.593550 | 3.913500 | 4.289500 | 35.319800 |
| 557 | 18.000000 | 4.297494 | 12.489783 | 0.000000 | 1.141675 | 1.288800 | 1.823525 | 54.291700 |
| 558 | 18.000000 | 1.057100 | 0.178253 | 0.912800 | 0.949075 | 0.971450 | 1.129575 | 1.502100 |
| 559 | 18.000000 | 0.365217 | 0.231510 | 0.113900 | 0.152825 | 0.330900 | 0.461900 | 0.728800 |
| 560 | 18.000000 | 0.107783 | 0.094416 | 0.026700 | 0.039100 | 0.067600 | 0.118450 | 0.272200 |
| 561 | 18.000000 | 33.178556 | 18.131571 | 12.429500 | 16.385575 | 27.690050 | 49.359400 | 62.757200 |
| 562 | 18.000000 | 161.125111 | 132.296562 | 0.000000 | 0.000000 | 260.841000 | 265.160500 | 268.228000 |
| 563 | 18.000000 | 0.424300 | 0.360367 | 0.000000 | 0.000000 | 0.582650 | 0.655900 | 0.903200 |
| 564 | 18.000000 | 3.256111 | 3.290021 | 0.000000 | 0.000000 | 2.715000 | 5.992500 | 9.260000 |
| 565 | 18.000000 | 0.104811 | 0.147407 | 0.000000 | 0.000000 | 0.097250 | 0.130650 | 0.621900 |
| 566 | 18.000000 | 1.363594 | 1.381565 | 0.000000 | 0.000000 | 1.148850 | 2.298875 | 3.561100 |
| 567 | 18.000000 | 0.042267 | 0.060458 | 0.000000 | 0.000000 | 0.038450 | 0.051075 | 0.256200 |
| 568 | 18.000000 | 1.233628 | 1.241228 | 0.000000 | 0.000000 | 1.028450 | 2.263275 | 3.482200 |
| 569 | 18.000000 | 14.171222 | 16.992290 | 0.000000 | 0.000000 | 14.227000 | 21.917575 | 68.848900 |
| 570 | 18.000000 | 531.775356 | 10.051614 | 493.005400 | 532.055725 | 533.583200 | 535.022475 | 541.903600 |
| 571 | 18.000000 | 2.177911 | 0.153724 | 1.871500 | 2.049800 | 2.193650 | 2.275550 | 2.433500 |
| 572 | 18.000000 | 23.571106 | 63.573740 | 3.540000 | 7.912500 | 8.930000 | 9.945000 | 278.190000 |
| 573 | 18.000000 | 0.271161 | 0.085763 | 0.129100 | 0.207625 | 0.275400 | 0.316525 | 0.483900 |
| 574 | 18.000000 | 7.837844 | 21.162363 | 1.039500 | 2.531250 | 2.890000 | 3.421200 | 92.586600 |
| 575 | 18.000000 | 0.084078 | 0.025303 | 0.046900 | 0.065650 | 0.085150 | 0.095250 | 0.134300 |
| 576 | 18.000000 | 4.655272 | 12.925751 | 0.663600 | 1.479450 | 1.672200 | 1.873075 | 56.427400 |
| 577 | 18.000000 | 12.428100 | 3.801384 | 6.557700 | 9.679150 | 12.632800 | 14.485325 | 22.148000 |
| 578 | 18.000000 | 0.017911 | 0.015953 | 0.000000 | 0.002400 | 0.018600 | 0.021000 | 0.058400 |
| 579 | 18.000000 | 0.014944 | 0.012677 | 0.000000 | 0.002450 | 0.015100 | 0.019925 | 0.048400 |
| 580 | 18.000000 | 0.004678 | 0.003887 | 0.000000 | 0.000850 | 0.004500 | 0.006900 | 0.014800 |
| 581 | 18.000000 | 67.590761 | 56.358387 | 0.000000 | 11.001925 | 74.675450 | 93.830600 | 208.204500 |
| 582 | 18.000000 | 0.498478 | 0.005998 | 0.480000 | 0.496025 | 0.499150 | 0.501375 | 0.507700 |
| 583 | 18.000000 | 0.041128 | 0.108953 | 0.007800 | 0.010650 | 0.015150 | 0.016850 | 0.476600 |
| 584 | 18.000000 | 0.009572 | 0.023741 | 0.002100 | 0.003400 | 0.003850 | 0.004350 | 0.104500 |
| 585 | 18.000000 | 8.454061 | 22.725950 | 1.535200 | 2.133925 | 3.037500 | 3.387075 | 99.303200 |
| 586 | 18.000000 | 0.023000 | 0.012945 | 0.000000 | 0.018400 | 0.020200 | 0.030950 | 0.058400 |
| 587 | 18.000000 | 0.017994 | 0.009994 | 0.000000 | 0.014900 | 0.015100 | 0.019925 | 0.048400 |
| 588 | 18.000000 | 0.005633 | 0.003020 | 0.000000 | 0.004250 | 0.004850 | 0.006900 | 0.014800 |
| 589 | 18.000000 | 81.599300 | 44.213851 | 0.000000 | 53.605975 | 78.803300 | 93.830600 | 208.204500 |
def boxhistplot(columns,data):
fig = px.histogram(Future, x = Future[column], color = 'Time')
fig.show()
col = ['159','160','161','225','294','295','296','297']
for column in col:
boxhistplot(column, data)
Future2 = Future.drop('Time', axis=1)
Future['Time'] = Future['Time'].apply(str)
print()
print(Future.dtypes)
Future
Time object
0 float64
1 float64
2 float64
3 float64
...
585 float64
586 float64
587 float64
588 float64
589 float64
Length: 591, dtype: object
| Time | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ... | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 19-07-2008 11:55 | 3030.93 | 2564.00 | 2187.7333 | 1411.1265 | 1.3602 | 100 | 97.6133 | 0.1242 | 1.5005 | ... | 0.0000 | 0.0000 | 0.5005 | 0.0118 | 0.0035 | 2.3630 | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
| 1 | 19-07-2008 12:32 | 3095.78 | 2465.14 | 2230.4222 | 1463.6606 | 0.8294 | 100 | 102.3433 | 0.1247 | 1.4966 | ... | 0.0060 | 208.2045 | 0.5019 | 0.0223 | 0.0055 | 4.4447 | 0.0096 | 0.0201 | 0.0060 | 208.2045 |
| 2 | 19-07-2008 13:17 | 2932.61 | 2559.94 | 2186.4111 | 1698.0172 | 1.5102 | 100 | 95.4878 | 0.1241 | 1.4436 | ... | 0.0148 | 82.8602 | 0.4958 | 0.0157 | 0.0039 | 3.1745 | 0.0584 | 0.0484 | 0.0148 | 82.8602 |
| 3 | 19-07-2008 14:43 | 2988.72 | 2479.90 | 2199.0333 | 909.7926 | 1.3204 | 100 | 104.2367 | 0.1217 | 1.4882 | ... | 0.0044 | 73.8432 | 0.4990 | 0.0103 | 0.0025 | 2.0544 | 0.0202 | 0.0149 | 0.0044 | 73.8432 |
| 4 | 19-07-2008 15:22 | 3032.24 | 2502.87 | 2233.3667 | 1326.5200 | 1.5334 | 100 | 100.3967 | 0.1235 | 1.5031 | ... | 0.0000 | 0.0000 | 0.4800 | 0.4766 | 0.1045 | 99.3032 | 0.0202 | 0.0149 | 0.0044 | 73.8432 |
| 5 | 19-07-2008 17:53 | 2946.25 | 2432.84 | 2233.3667 | 1326.5200 | 1.5334 | 100 | 100.3967 | 0.1235 | 1.5287 | ... | 0.0052 | 44.0077 | 0.4949 | 0.0189 | 0.0044 | 3.8276 | 0.0342 | 0.0151 | 0.0052 | 44.0077 |
| 6 | 19-07-2008 19:44 | 3030.27 | 2430.12 | 2230.4222 | 1463.6606 | 0.8294 | 100 | 102.3433 | 0.1247 | 1.5816 | ... | 0.0000 | 0.0000 | 0.5010 | 0.0143 | 0.0042 | 2.8515 | 0.0342 | 0.0151 | 0.0052 | 44.0077 |
| 7 | 19-07-2008 19:45 | 3058.88 | 2690.15 | 2248.9000 | 1004.4692 | 0.7884 | 100 | 106.2400 | 0.1185 | 1.5153 | ... | 0.0063 | 95.0310 | 0.4984 | 0.0106 | 0.0034 | 2.1261 | 0.0204 | 0.0194 | 0.0063 | 95.0310 |
| 8 | 19-07-2008 20:24 | 2967.68 | 2600.47 | 2248.9000 | 1004.4692 | 0.7884 | 100 | 106.2400 | 0.1185 | 1.5358 | ... | 0.0045 | 111.6525 | 0.4993 | 0.0172 | 0.0046 | 3.4456 | 0.0111 | 0.0124 | 0.0045 | 111.6525 |
| 9 | 19-07-2008 21:35 | 3016.11 | 2428.37 | 2248.9000 | 1004.4692 | 0.7884 | 100 | 106.2400 | 0.1185 | 1.5381 | ... | 0.0073 | 90.2294 | 0.4967 | 0.0152 | 0.0038 | 3.0687 | 0.0212 | 0.0191 | 0.0073 | 90.2294 |
| 10 | 19-07-2008 21:57 | 2994.05 | 2548.21 | 2195.1222 | 1046.1468 | 1.3204 | 100 | 103.3400 | 0.1223 | 1.5144 | ... | 0.0071 | 57.8122 | 0.4925 | 0.0158 | 0.0041 | 3.2115 | 0.0355 | 0.0205 | 0.0071 | 57.8122 |
| 11 | 19-07-2008 22:52 | 2928.84 | 2479.40 | 2196.2111 | 1605.7578 | 0.9959 | 100 | 97.9156 | 0.1257 | 1.4690 | ... | 0.0081 | 75.5077 | 0.4987 | 0.0427 | 0.0092 | 8.5646 | 0.0370 | 0.0279 | 0.0081 | 75.5077 |
| 12 | 20-07-2008 03:35 | 2920.07 | 2507.40 | 2195.1222 | 1046.1468 | 1.3204 | 100 | 103.3400 | 0.1223 | 1.5310 | ... | 0.0034 | 52.2039 | 0.4950 | 0.0153 | 0.0041 | 3.0926 | 0.0188 | 0.0098 | 0.0034 | 52.2039 |
| 13 | 21-07-2008 08:21 | 3051.44 | 2529.27 | 2184.4333 | 877.6266 | 1.4668 | 100 | 107.8711 | 0.1240 | 1.5236 | ... | 0.0000 | 0.0000 | 0.5034 | 0.0151 | 0.0038 | 3.0063 | 0.0188 | 0.0098 | 0.0034 | 52.2039 |
| 14 | 21-07-2008 11:53 | 2963.97 | 2629.48 | 2224.6222 | 947.7739 | 1.2924 | 100 | 104.8489 | 0.1197 | 1.4474 | ... | 0.0084 | 142.9080 | 0.5077 | 0.0094 | 0.0026 | 1.8483 | 0.0202 | 0.0289 | 0.0084 | 142.9080 |
| 15 | 22-07-2008 00:03 | 2988.31 | 2546.26 | 2224.6222 | 947.7739 | 1.2924 | 100 | 104.8489 | 0.1197 | 1.5465 | ... | 0.0045 | 100.2745 | 0.5058 | 0.0078 | 0.0021 | 1.5352 | 0.0174 | 0.0174 | 0.0045 | 100.2745 |
| 16 | 22-07-2008 02:59 | 3028.02 | 2560.87 | 2270.2556 | 1258.4558 | 1.3950 | 100 | 104.8078 | 0.1207 | 1.4368 | ... | 0.0042 | 82.0989 | 0.5005 | 0.0108 | 0.0034 | 2.1574 | 0.0184 | 0.0151 | 0.0042 | 82.0989 |
| 17 | 22-07-2008 08:41 | 3032.73 | 2517.79 | 2270.2556 | 1258.4558 | 1.3950 | 100 | 104.8078 | 0.1207 | 1.5537 | ... | 0.0000 | 0.0000 | 0.5015 | 0.0105 | 0.0027 | 2.0979 | 0.0184 | 0.0151 | 0.0042 | 82.0989 |
18 rows × 591 columns
from sklearn.preprocessing import normalize
X = Future2
y = Future['Time']
X = X.dropna(thresh=30)
X = X.fillna(method='backfill')
X = normalize(X)
X = X[(np.max(X, axis=1) - np.min(X, axis=1)) / np.min(X, axis=1) < 10**2, :]
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4)
from imblearn.over_sampling import RandomOverSampler
ros = RandomOverSampler()
X_ros, y_ros = ros.fit_resample(X_train, y_train)
y_ros
0 19-07-2008 12:32 1 19-07-2008 21:35 2 19-07-2008 20:24 3 19-07-2008 19:45 4 22-07-2008 00:03 5 21-07-2008 08:21 6 19-07-2008 21:57 7 19-07-2008 15:22 8 19-07-2008 22:52 9 22-07-2008 02:59 Name: Time, dtype: object
X_ros
array([[2.30256458e-01, 1.83351015e-01, 1.65893285e-01, ...,
1.49498827e-06, 4.46265157e-07, 1.54857356e-02],
[2.24141629e-01, 1.80463845e-01, 1.67126567e-01, ...,
1.41941279e-06, 5.42498082e-07, 6.70538034e-03],
[2.00561455e-01, 1.75744706e-01, 1.51984937e-01, ...,
8.38015570e-07, 3.04118554e-07, 7.54568818e-03],
...,
[2.23398366e-01, 1.84397365e-01, 1.64541880e-01, ...,
1.09774808e-06, 3.24167219e-07, 5.44035109e-03],
[2.15124890e-01, 1.82113277e-01, 1.61312899e-01, ...,
2.04927016e-06, 5.94949401e-07, 5.54608160e-03],
[2.25390431e-01, 1.90618157e-01, 1.68986297e-01, ...,
1.12396731e-06, 3.12626670e-07, 6.11102517e-03]])
y_ros.shape
(10,)
X_ros.shape
(10, 590)
df_ros, y_resampled2 = ros.fit_resample(X_train, y_train)
y_resampled2.head()
0 19-07-2008 12:32 1 19-07-2008 21:35 2 19-07-2008 20:24 3 19-07-2008 19:45 4 22-07-2008 00:03 Name: Time, dtype: object
df_ros.shape
(10, 590)
df_OS = pd.DataFrame(X_ros)
df_OS.head()
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ... | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.230256 | 0.183351 | 0.165893 | 0.108863 | 0.000062 | 0.007438 | 0.007612 | 0.000009 | 0.000111 | -3.718876e-08 | ... | 4.462652e-07 | 0.015486 | 0.000037 | 1.658619e-06 | 4.090764e-07 | 0.000331 | 7.140243e-07 | 1.494988e-06 | 4.462652e-07 | 0.015486 |
| 1 | 0.224142 | 0.180464 | 0.167127 | 0.074647 | 0.000059 | 0.007431 | 0.007895 | 0.000009 | 0.000114 | 1.181605e-06 | ... | 5.424981e-07 | 0.006705 | 0.000037 | 1.129585e-06 | 2.823963e-07 | 0.000228 | 1.575474e-06 | 1.419413e-06 | 5.424981e-07 | 0.006705 |
| 2 | 0.200561 | 0.175745 | 0.151985 | 0.067884 | 0.000053 | 0.006758 | 0.007180 | 0.000008 | 0.000104 | 7.501591e-07 | ... | 3.041186e-07 | 0.007546 | 0.000034 | 1.162409e-06 | 3.108767e-07 | 0.000233 | 7.501591e-07 | 8.380156e-07 | 3.041186e-07 | 0.007546 |
| 3 | 0.228587 | 0.201032 | 0.168058 | 0.075063 | 0.000059 | 0.007473 | 0.007939 | 0.000009 | 0.000113 | 1.173245e-06 | ... | 4.707926e-07 | 0.007102 | 0.000037 | 7.921272e-07 | 2.540785e-07 | 0.000159 | 1.524471e-06 | 1.449742e-06 | 4.707926e-07 | 0.007102 |
| 4 | 0.201875 | 0.172012 | 0.150284 | 0.064027 | 0.000087 | 0.006755 | 0.007083 | 0.000008 | 0.000104 | 1.688872e-06 | ... | 3.039970e-07 | 0.006774 | 0.000034 | 5.269281e-07 | 1.418653e-07 | 0.000104 | 1.175455e-06 | 1.175455e-06 | 3.039970e-07 | 0.006774 |
5 rows × 590 columns
df_OS_y = pd.DataFrame(y_resampled2)
df_OS_y.shape
(10, 1)
frames4 = [df_OS, y_resampled2]
result4 = pd.concat(frames4)
result4.head()
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ... | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.230256 | 0.183351 | 0.165893 | 0.108863 | 0.000062 | 0.007438 | 0.007612 | 0.000009 | 0.000111 | -3.718876e-08 | ... | 4.462652e-07 | 0.015486 | 0.000037 | 1.658619e-06 | 4.090764e-07 | 0.000331 | 7.140243e-07 | 1.494988e-06 | 4.462652e-07 | 0.015486 |
| 1 | 0.224142 | 0.180464 | 0.167127 | 0.074647 | 0.000059 | 0.007431 | 0.007895 | 0.000009 | 0.000114 | 1.181605e-06 | ... | 5.424981e-07 | 0.006705 | 0.000037 | 1.129585e-06 | 2.823963e-07 | 0.000228 | 1.575474e-06 | 1.419413e-06 | 5.424981e-07 | 0.006705 |
| 2 | 0.200561 | 0.175745 | 0.151985 | 0.067884 | 0.000053 | 0.006758 | 0.007180 | 0.000008 | 0.000104 | 7.501591e-07 | ... | 3.041186e-07 | 0.007546 | 0.000034 | 1.162409e-06 | 3.108767e-07 | 0.000233 | 7.501591e-07 | 8.380156e-07 | 3.041186e-07 | 0.007546 |
| 3 | 0.228587 | 0.201032 | 0.168058 | 0.075063 | 0.000059 | 0.007473 | 0.007939 | 0.000009 | 0.000113 | 1.173245e-06 | ... | 4.707926e-07 | 0.007102 | 0.000037 | 7.921272e-07 | 2.540785e-07 | 0.000159 | 1.524471e-06 | 1.449742e-06 | 4.707926e-07 | 0.007102 |
| 4 | 0.201875 | 0.172012 | 0.150284 | 0.064027 | 0.000087 | 0.006755 | 0.007083 | 0.000008 | 0.000104 | 1.688872e-06 | ... | 3.039970e-07 | 0.006774 | 0.000034 | 5.269281e-07 | 1.418653e-07 | 0.000104 | 1.175455e-06 | 1.175455e-06 | 3.039970e-07 | 0.006774 |
5 rows × 590 columns
result4.to_csv('OS_Future.csv', index=False)
Future_OS = pd.read_csv('OS_Future.csv')
Future_OS.head()
| Time | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ... | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 19-07-2008 12:32 | 0.230256 | 0.183351 | 0.165893 | 0.108863 | 0.000062 | 0.007438 | 0.007612 | 0.000009 | 0.000111 | ... | 4.460000e-07 | 0.015486 | 0.000037 | 1.660000e-06 | 4.090000e-07 | 0.000331 | 7.140000e-07 | 1.490000e-06 | 4.460000e-07 | 0.015486 |
| 1 | 19-07-2008 21:35 | 0.224142 | 0.180464 | 0.167127 | 0.074647 | 0.000059 | 0.007431 | 0.007895 | 0.000009 | 0.000114 | ... | 5.420000e-07 | 0.006705 | 0.000037 | 1.130000e-06 | 2.820000e-07 | 0.000228 | 1.580000e-06 | 1.420000e-06 | 5.420000e-07 | 0.006705 |
| 2 | 19-07-2008 20:24 | 0.200561 | 0.175745 | 0.151985 | 0.067884 | 0.000053 | 0.006758 | 0.007180 | 0.000008 | 0.000104 | ... | 3.040000e-07 | 0.007546 | 0.000034 | 1.160000e-06 | 3.110000e-07 | 0.000233 | 7.500000e-07 | 8.380000e-07 | 3.040000e-07 | 0.007546 |
| 3 | 19-07-2008 19:45 | 0.228587 | 0.201032 | 0.168058 | 0.075063 | 0.000059 | 0.007473 | 0.007939 | 0.000009 | 0.000113 | ... | 4.710000e-07 | 0.007102 | 0.000037 | 7.920000e-07 | 2.540000e-07 | 0.000159 | 1.520000e-06 | 1.450000e-06 | 4.710000e-07 | 0.007102 |
| 4 | 22-07-2008 00:03 | 0.201875 | 0.172012 | 0.150284 | 0.064027 | 0.000087 | 0.006755 | 0.007083 | 0.000008 | 0.000104 | ... | 3.040000e-07 | 0.006774 | 0.000034 | 5.270000e-07 | 1.420000e-07 | 0.000104 | 1.180000e-06 | 1.180000e-06 | 3.040000e-07 | 0.006774 |
5 rows × 591 columns
from sdv.tabular import GaussianCopula
import pandas as pd
import numpy as np
real_data = pd.read_csv('OS_Future.csv')
import warnings
warnings.filterwarnings("ignore")
model = GaussianCopula()
model.fit(real_data)
synthetic_data = model.sample()
real_data.head()
| Time | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ... | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 19-07-2008 12:32 | 0.230256 | 0.183351 | 0.165893 | 0.108863 | 0.000062 | 0.007438 | 0.007612 | 0.000009 | 0.000111 | ... | 4.460000e-07 | 0.015486 | 0.000037 | 1.660000e-06 | 4.090000e-07 | 0.000331 | 7.140000e-07 | 1.490000e-06 | 4.460000e-07 | 0.015486 |
| 1 | 19-07-2008 21:35 | 0.224142 | 0.180464 | 0.167127 | 0.074647 | 0.000059 | 0.007431 | 0.007895 | 0.000009 | 0.000114 | ... | 5.420000e-07 | 0.006705 | 0.000037 | 1.130000e-06 | 2.820000e-07 | 0.000228 | 1.580000e-06 | 1.420000e-06 | 5.420000e-07 | 0.006705 |
| 2 | 19-07-2008 20:24 | 0.200561 | 0.175745 | 0.151985 | 0.067884 | 0.000053 | 0.006758 | 0.007180 | 0.000008 | 0.000104 | ... | 3.040000e-07 | 0.007546 | 0.000034 | 1.160000e-06 | 3.110000e-07 | 0.000233 | 7.500000e-07 | 8.380000e-07 | 3.040000e-07 | 0.007546 |
| 3 | 19-07-2008 19:45 | 0.228587 | 0.201032 | 0.168058 | 0.075063 | 0.000059 | 0.007473 | 0.007939 | 0.000009 | 0.000113 | ... | 4.710000e-07 | 0.007102 | 0.000037 | 7.920000e-07 | 2.540000e-07 | 0.000159 | 1.520000e-06 | 1.450000e-06 | 4.710000e-07 | 0.007102 |
| 4 | 22-07-2008 00:03 | 0.201875 | 0.172012 | 0.150284 | 0.064027 | 0.000087 | 0.006755 | 0.007083 | 0.000008 | 0.000104 | ... | 3.040000e-07 | 0.006774 | 0.000034 | 5.270000e-07 | 1.420000e-07 | 0.000104 | 1.180000e-06 | 1.180000e-06 | 3.040000e-07 | 0.006774 |
5 rows × 591 columns
synthetic_data.head()
| Time | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ... | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 22-07-2008 02:59 | 0.219106 | 0.183945 | 0.165843 | 0.064303 | 0.000091 | 0.007083 | 0.007477 | 0.000009 | 0.000107 | ... | 2.487798e-07 | 0.005865 | 0.000036 | 5.270000e-07 | 1.420000e-07 | 0.000104 | 1.263629e-06 | 8.561509e-07 | 2.638135e-07 | 0.005311 |
| 1 | 19-07-2008 12:32 | 0.230256 | 0.189138 | 0.168258 | 0.064354 | 0.000098 | 0.007473 | 0.007680 | 0.000009 | 0.000113 | ... | 2.643114e-07 | 0.007258 | 0.000037 | 6.717715e-07 | 2.114669e-07 | 0.000134 | 8.519875e-07 | 1.067073e-06 | 2.531014e-07 | 0.007175 |
| 2 | 19-07-2008 20:24 | 0.212472 | 0.176787 | 0.161572 | 0.068230 | 0.000104 | 0.006999 | 0.007145 | 0.000009 | 0.000105 | ... | 2.188497e-07 | 0.002594 | 0.000034 | 1.535358e-06 | 3.656429e-07 | 0.000311 | 1.510239e-06 | 9.095515e-07 | 2.943355e-07 | 0.003905 |
| 3 | 19-07-2008 15:22 | 0.230256 | 0.201032 | 0.168952 | 0.091831 | 0.000113 | 0.007473 | 0.007939 | 0.000009 | 0.000114 | ... | 2.875805e-07 | 0.000000 | 0.000037 | 4.640143e-06 | 1.087662e-06 | 0.000933 | 2.230264e-06 | 1.538976e-06 | 3.797223e-07 | 0.004134 |
| 4 | 19-07-2008 12:32 | 0.223451 | 0.181579 | 0.156523 | 0.088441 | 0.000063 | 0.007105 | 0.007180 | 0.000009 | 0.000105 | ... | 2.040188e-07 | 0.012264 | 0.000037 | 1.463119e-06 | 3.699944e-07 | 0.000294 | 7.140000e-07 | 1.092889e-06 | 3.781918e-07 | 0.012637 |
5 rows × 591 columns
from sdv.evaluation import evaluate
evaluate(synthetic_data, real_data)
0.8045733158442578
evaluate(synthetic_data, real_data, aggregate=False)
| metric | name | raw_score | normalized_score | min_value | max_value | goal | |
|---|---|---|---|---|---|---|---|
| 1 | LogisticDetection | LogisticRegression Detection | 1.000000 | 1.000000 | 0.0 | 1.0 | MAXIMIZE |
| 2 | SVCDetection | SVC Detection | 0.740741 | 0.740741 | 0.0 | 1.0 | MAXIMIZE |
| 11 | GMLogLikelihood | GaussianMixture Log Likelihood | 3327.288192 | 1.000000 | -inf | inf | MAXIMIZE |
| 12 | CSTest | Chi-Squared | 0.999438 | 0.999438 | 0.0 | 1.0 | MAXIMIZE |
| 13 | KSTest | Inverted Kolmogorov-Smirnov D statistic | 0.776780 | 0.776780 | 0.0 | 1.0 | MAXIMIZE |
| 14 | KSTestExtended | Inverted Kolmogorov-Smirnov D statistic | 0.776819 | 0.776819 | 0.0 | 1.0 | MAXIMIZE |
| 27 | ContinuousKLDivergence | Continuous Kullback–Leibler Divergence | 0.245644 | 0.245644 | 0.0 | 1.0 | MAXIMIZE |
evaluate(synthetic_data, real_data, metrics=['CSTest', 'KSTest'])
0.8881085818573908
from sdv.metrics.tabular import LogisticDetection, SVCDetection
LogisticDetection.compute(real_data, synthetic_data)
0.4629629629629629
SVCDetection.compute(real_data, synthetic_data)
0.33333333333333337
from sdv.metrics.tabular import BinaryLogisticRegression
BinaryLogisticRegression.compute(real_data, synthetic_data, target='Time')
0.5
train = synthetic_data.sample(int(len(real_data) * 0.75))
test = synthetic_data[~synthetic_data.index.isin(train.index)]
BinaryLogisticRegression.compute(test, train, target='Time')
0.6666666666666666
train = real_data.sample(int(len(real_data) * 0.75))
test = real_data[~real_data.index.isin(train.index)]
BinaryLogisticRegression.compute(test, train, target='Time')
0.0
Using Random oversampling the future data has been generated. Using SDV the synthetic data has been generated on Oversampling data.We got 60% score on Binary logistic regression from synthetic over sampling data.
Bivariate graphs show that, sensors stopped working due to some technical issue. The data generated was zero in that specific time. Random Oversampling and SMOTE were best Cross validation techniques which has got highest accuracy score. From various Hyper Parameter tuning techniques the Gradient Boost and Support vector machine has highest accuracy score. PCA dimenstionality reduction has not improved the modelling in this data set. However, the components which were analysed has got the best scores despite of reducing the data.
Multiple rows in the data set are not fit for analysis. Though, the data set is huge but it was very easy to train, validate and test.